Author: L. T. Koczy

Robot cooperation without explicit communication by fuzzy signatures and decision trees

Publication Name: 2009 International Fuzzy Systems Association World Congress and 2009 European Society for Fuzzy Logic and Technology Conference Ifsa Eusflat 2009 Proceedings

Publication Date: 2009-12-01

Volume: Unknown

Issue: Unknown

Page Range: 1468-1473

Description:

This paper presents a novel action selection method for multi robot task sharing problem. Two autonomous mobile robots try to cooperate for push a box to a goal position. Both robots equipped with object and goal sensing, but do not have explicit communication ability. We explore the use of fuzzy signatures and decision making system to intention guessing and efficient action selection. Virtual reality simulation is used to build and test our proposed algorithm.

Open Access: Yes

DOI: DOI not available

Optimization in fuzzy flip-flop neural networks

László Gál Rita Lovassy L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2010-11-03

Volume: 313

Issue: Unknown

Page Range: 337-348

Description:

The fuzzy J-K and D flip-flops present s-shape transfer characteristics in same particular cases. We propose the fuzzy flip-flop neurons; single input-single output units derived from fuzzy flip-flops as sigmoid function generators. The fuzzy neurons-based neural networks, Fuzzy Flip-Flop Neural Networks (FNN) parameters are quasi optimized using a second-order gradient algorithm, the Levenberg-Marquardt method (LM) and an evolutionary algorithm, the Bacterial Memetic Algorithm with Modified Operator Execution Order (BMAM). The quasi optimized FNN's performance based on Dombi and Yager fuzzy operations has been examined with a series of test functions. © 2010 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-642-15220-7_27

Robot cooperation by fuzzy signature sets rule base

Á Ballagi L. T. Koczy

Publication Name: Sami 2010 8th International Symposium on Applied Machine Intelligence and Informatics Proceedings

Publication Date: 2010-04-30

Volume: Unknown

Issue: Unknown

Page Range: 37-42

Description:

This paper presents a novel method for control cooperating robots without any explicit communication line. We have proposed a fuzzy communication philosophy and implementation technique, where the codebooks are built up by signatures. Fuzzy signatures are used as complex state description method for intention guessing and action selection. Finally some real scenarios of autonomous mobile robot cooperation are presented. ©2010 IEEE.

Open Access: Yes

DOI: 10.1109/SAMI.2010.5423703

Exploiting the functional training approach in takagi-sugeno neuro-fuzzy systems

Pedro M. Ferreira C. Cabrita A. E. Ruano L. T. Koczy

Publication Name: Advances in Intelligent Systems and Computing

Publication Date: 2013-01-01

Volume: 195 AISC

Issue: Unknown

Page Range: 543-559

Description:

When used for function approximation purposes, neural networks and neuro-fuzzy systems belong to a class of models whose parameters can be separated into linear and nonlinear, according to their influence in the model output. This concept of parameter separability can also be applied when the training problem is formulated as the minimization of the integral of the (functional) squared error, over the input domain. Using this approach, the computation of the derivatives involves terms that are dependent only on the model and the input domain, and terms which are the projection of the target function on the basis functions and on their derivatives with respect to the nonlinear parameters, over the input domain. These later terms can be numerically computed with the data. The use of the functional approach is introduced here for Takagi-Sugeno models. An example shows that this approach obtains better results than the standard, discrete technique, as the performance surface employed is more similar to the one obtained with the function underlying the data. In some cases, as shown in the example, a complete analytical solution can be found. © 2013 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-642-33941-7_48

Bacterial memetic algorithm for fuzzy rule base optimization

C. Cabrita J. Botzheim T. D. Gedeon Carlos Fonseca A. E. Ruano L. T. Koczy

Publication Name: 2006 World Automation Congress Wac 06

Publication Date: 2006-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

In our previous works model identification methods were discussed. The bacterial evolutionary algorithm for extracting a fuzzy rule base from a training set was presented. The LevenbergMarquardt method was also proposed for determining membership functions in fuzzy systems. The combination of evolutionary and gradient-based learning techniques - the bacterial memetic algorithm - was also introduced. In this paper an improvement of the bacterial memetic algorithm is shown for fuzzy rule extraction. The new method can optimize not only the rules, but can also find the optimal size of the rule base. Copyright - World Automation Congress (WAC) 2006.

Open Access: Yes

DOI: 10.1109/WAC.2006.376057

An hybrid training method for B-spline neural networks

C. Cabrita J. Botzheim A. E. Ruano L. T. Koczy

Publication Name: 2005 IEEE International Workshop on Intelligent Signal Processing Proceedings

Publication Date: 2005-12-01

Volume: Unknown

Issue: Unknown

Page Range: 165-170

Description:

Current and past research has brought up new views related to the optimization of neural networks. For a fixed structure, second order methods are seen as the most promising. From previous works we have shown how second order methods are of easy applicability to a neural network. Namely, we have proved how the Levenberg-Marquard possesses not only better convergence but how it can assure the convergence to a local minima. However, as any gradient-based method, the results obtained depend on the startup point. In this work, a reformulated Evolutionary algorithm - the Bacterial Programming for Levenberg-Marquardt is proposed, as an heuristic which can be used to determine the most suitable starting points, therefore achieving, in most cases, the global optimum. © 2005 IEEE.

Open Access: Yes

DOI: DOI not available

Sensitivity and validity of the fuzzy signature based evaluation of residential building conditions

Ádám Bukovics István Harmati L. T. Koczy

Publication Name: Civil Comp Proceedings

Publication Date: 2014-01-01

Volume: 105

Issue: Unknown

Page Range: Unknown

Description:

The characteristics and the status of the existing stock of residential buildings are extremely important for the national economy of all countries including Hungary. Formerly some methods and approaches to formally tackle and evaluate individual buildings based on available records and expert reports were formulated. These methods are suitable for the evaluation and ranking of residential buildings and make it easier to complete the status assessment and decision support for further utilization. A mathematical analysis has been conducted to identify the sensitivity of the calculated final results in the case of the applied fuzzy signatures related to the changes of the membership values at the leaves (the end nodes of a graph). This paper briefly presents the methods, then it investigates the validity of these results taking into consideration the possible subjective discrepancy and certainty in the evaluations.

Open Access: Yes

DOI: DOI not available

Modeling integrated sustainable waste management systems using fuzzy cognitive maps and systems of systems concepts

F. Hatwágner A. Buruzs L. T. Koczy

Publication Name: Civil Comp Proceedings

Publication Date: 2014-01-01

Volume: 105

Issue: Unknown

Page Range: Unknown

Description:

Movement towards more sustainable waste management practice has been identified as a priority in the whole of the EU. The EU Waste Management Strategy's requirements emphasizes waste prevention; recycling and reuse; and improving final disposal and monitoring. Integrated waste management systems can be defined as the selection and application of suitable and available techniques, technologies and management programs to achieve waste management objectives and goals. As a result of the complexity and uncertainty occurring in sustainable waste management systems, the fuzzy cognitive map method is used with the combination of the bacterial evolutionary algorithm to support the planning and decision making process of integrated systems. Since the fuzzy cognitive map method is formed for a selected system by determining the concepts and their relationships, it is possible to quantitatively simulate the system considering its parameters. Several techniques were used in order to produce the input data of the simulation process. The goal of this paper is to present the process of data production.

Open Access: Yes

DOI: DOI not available

Comparative analysis of interpolative and non-interpolative fuzzy rule based machine learning systems applying various numerical optimization methods

J. Botzheim Krisztián Balázs L. T. Koczy

Publication Name: 2010 IEEE World Congress on Computational Intelligence Wcci 2010

Publication Date: 2010-11-25

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

In this paper interpolative and non-interpolative fuzzy rule based machine learning systems are investigated by using simulation results. The investigation focuses mainly on two objectives: to compare the efficiency of the inference techniques combined with different numerical optimization methods for solving machine learning problems and to discover the difference between the properties of systems applying interpolative and non-interpolative inference techniques. © 2010 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2010.5584156

Improving system reliability in optical networks by failure localization using evolutionary optimization

Péter Soproni Krisztián Balázs L. T. Koczy

Publication Name: Syscon 2013 7th Annual IEEE International Systems Conference Proceedings

Publication Date: 2013-08-30

Volume: Unknown

Issue: Unknown

Page Range: 394-399

Description:

This paper proposes a novel approach for cost-effective link failure localization in optical networks in order to improve the reliability of telecommunication systems. In such failure localization problems the optical network is usually represented by a graph, where the task is to form connected edge sets, so-called monitoring trails (m-trails), in a way that the failure of a link causes the failure of such a combination of m-trails, which unambiguously identifies the failed link. Every m-trail consumes a given amount of resources (like bandwidth, detectors, amplifiers, etc.). Thus, operators of optical network may prefer a set of paths, whose paths can be established in an easy and cost-effective way, while minimizing the interference with the route of the existing demands, i.e. may maximize the revenue. In this paper, unlike most existing techniques dealing with failure localization in this context, the presently proposed method considers a predefined set of paths in the graph as m-trails. This way the task can also be formulated as a special Set Covering Problem (SCP), whose general form is a frequently used formulation in a certain type of operations research problems (e.g. resource assignment). Since for the SCP task evolutionary algorithms, like Ant Colony Optimization (ACO), has been successfully applied in the operations research field, in this work the failure localization task is solved by using ACO on the SCP formulation of the described covering problem, which is a rather unique combination of approaches of different fields (telecommunication, operations research and evolutionary computation) placing our investigation in the multi-field scope of complex systems. © 2013 IEEE.

Open Access: Yes

DOI: 10.1109/SysCon.2013.6549912

Function approximation capability of a novel fuzzy flip-flop based Neural Network

László Gál Rita Lovassy L. T. Koczy

Publication Name: Proceedings of the International Joint Conference on Neural Networks

Publication Date: 2009-11-18

Volume: Unknown

Issue: Unknown

Page Range: 1900-1907

Description:

The function approximation capability of various connectionist systems has been one of the most interesting problems. A method for constructing Multilayer Perceptron Neural Networks (MLP NN) with the aid of fuzzy operations based flip-flops able to approximate single and multiple variable functions is proposed. This paper introduces the concept of fuzzy flip-flop based neural network, particularly by deploying three types of fuzzy flip-flops as neurons. A comparative study of feedbacked fuzzy J-K and two kinds of fuzzy D flip-flops used as neurons, based on fuzzy algebraic, Yager, Dombi, Hamacher and Frank operations is given. Simulation results are presented for several test functions. © 2009 IEEE.

Open Access: Yes

DOI: 10.1109/IJCNN.2009.5178849

Performance evaluation of wire pairs in telecommunications networks by fuzzy and evolutionary models

Ferenc Lilik L. T. Koczy

Publication Name: IEEE AFRICON Conference

Publication Date: 2013-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

This paper is dealing with a new approach for the performance evaluation of symmetrical wire pairs of telecommunications access networks. In this method the determination of the available data transmission rates is performed by fuzzy inference systems. The telecommunications environment and the physical parameters that influence the transmission are briefly reviewed. Two methods used for the creation of the rule bases and an easy way for the evaluation for the observations of the physical system are presented. © 2013 IEEE.

Open Access: Yes

DOI: 10.1109/AFRCON.2013.6757602

A kantian pattern of knowledge, the observation representation

R. C. Pozna Á Ballagi Radu Emil Precup L. T. Koczy

Publication Name: Siisy 2010 8th IEEE International Symposium on Intelligent Systems and Informatics

Publication Date: 2010-12-30

Volume: Unknown

Issue: Unknown

Page Range: 405-412

Description:

This paper suggests a new pattern of human knowledge. Its execution represents an important stage in the general framework of aiming the building of an artificial cognitive system. First the general presentation of the artificial cognitive system, its objective, main principles and implementation phases are highlighted. The known patterns, which have a cultural (philosophical, psychological and linguistic) origin are then analyzed. Finally the details concerning the proposed pattern are pointed out. ©2010 IEEE.

Open Access: Yes

DOI: 10.1109/SISY.2010.5647371

The application of fuzzy connectives and inverse operations on R-fuzzy descriptors of the static conditions of residential buildings

Ádám Bukovics L. T. Koczy

Publication Name: Cinti 2012 13th IEEE International Symposium on Computational Intelligence and Informatics Proceedings

Publication Date: 2012-12-01

Volume: Unknown

Issue: Unknown

Page Range: 433-437

Description:

A considerable part of the current stock of residential buildings in Budapest was built at the end of the 19^th and in the beginning of the 20^th century (Figure 1). In the course of our research work a great many detailed technical and static expert reports on residential buildings in Budapest built in this time period were available. On the basis of these expert reports a database was created for the purpose of analysis of the structure of the buildings and of building diagnostics (Figure 2), and in order to prepare a fuzzy signautre-based status defining and ranking model. The database was created by processing a reliable set of data, which, in this way is a large representative pattern, the analysis whereof enables us to draw scientific conclusions. So far nobody has processed the expert reports from the scientific point of view, so no synthetised results were available to date. © 2012 IEEE.

Open Access: Yes

DOI: 10.1109/CINTI.2012.6496805

Multi-threaded Bacterial Iterated Greedy heuristics for the Permutation Flow Shop Problem

Krisztián Balázs L. T. Koczy Zoltán Horváth

Publication Name: Cinti 2012 13th IEEE International Symposium on Computational Intelligence and Informatics Proceedings

Publication Date: 2012-12-01

Volume: Unknown

Issue: Unknown

Page Range: 63-66

Description:

This paper proposes approaches for combining Iterated Greedy techniques, as state-of-the-art methods, with bacterial evolutionary algorithms based on a hybrid technique involving the Multi-Threaded Iterated Greedy heuristic and a memetic algorithm in order to efficiently solve the Permutation Flow Shop Problem on parallel computing architectures. In the present work three novel approaches are proposed by combining a variant of the Bacterial Memetic Algorithm and the recently proposed Bacterial Iterated Greedy technique with the mentioned hybrid multi-threaded approach. The techniques thus obtained are evaluated via simulation runs carried out on a series of data from the well-known Taillard's benchmark problem set. Based on the experimental results the multi-threaded hybrid methods are compared to each other and to the original techniques (i.e. to the techniques without bacterial algorithms). © 2012 IEEE.

Open Access: Yes

DOI: 10.1109/CINTI.2012.6496734

Fuzzy Flip-Flop based Neural Networks as a novel implementation possibility of multilayer perceptrons

László Gál Rita Lovassy Árpád Tóth L. T. Koczy I. J. Rudas

Publication Name: 2012 IEEE I2mtc International Instrumentation and Measurement Technology Conference Proceedings

Publication Date: 2012-07-30

Volume: Unknown

Issue: Unknown

Page Range: 280-285

Description:

Fuzzy Flip-Flop based Neural Networks (FNN) constructed from fuzzy D flip-flops are studied as a novel technique to implement multilayer perceptrons. The starting point of this approach is the concept of fuzzy flip-flop (F ³), as the extension of the binary counterpart. Fuzzy D flip-flop based neurons are viewed, as sigmoid function generators. Their characteristic equations contain simple fuzzy operations, thus enabling easy implementability. FNNs have an interconnected fuzzy neuron structure composed from a large number of neurons acting in parallel which are capable of learning, and are suitable for function approximation. In this paper we propose the FPGA implementation of ukasiewicz operations, furthermore of fuzzy D flip-flop neurons based on Łukasiewicz norms. © 2012 IEEE.

Open Access: Yes

DOI: 10.1109/I2MTC.2012.6229326

Design of B-spline neural networks using a bacterial programming approach

C. Cabrita J. Botzheim A. E. Ruano L. T. Koczy

Publication Name: IEEE International Conference on Neural Networks Conference Proceedings

Publication Date: 2004-12-01

Volume: 3

Issue: Unknown

Page Range: 2313-2318

Description:

The design phase of B-spline neural networks represents a very high computational task. For this purpose, heuristics have been developed, but have been shown to be dependent on the initial conditions employed. In this paper a new technique, Bacterial Programming, is proposed, whose principles are based on the replication of the microbial evolution phenomenon. The performance of this approach is illustrated and compared with existing alternatives.

Open Access: Yes

DOI: 10.1109/IJCNN.2004.1380987

Exploiting the functional training approach in B-splines

Pedro M. Ferreira C. Cabrita A. E. Ruano L. T. Koczy

Publication Name: IFAC Proceedings Volumes IFAC Papersonline

Publication Date: 2012-01-01

Volume: 45

Issue: 4

Page Range: 127-132

Description:

When used for function approximation purposes, neural networks belong to a class of models whose parameters can be separated into linear and nonlinear, according to their influence in the model output. This concept of parameter separability can also be applied when the training problem is formulated as the minimization of the integral of the (functional) squared error, over the input domain. Using this approach, the computation of the gradient involves terms that are dependent only on the model and the input domain, and terms which are the projection of the target function on the basis functions and on their derivatives with respect to the nonlinear parameters, over the input domain. These later terms can be numerically computed with the data. The use of the functional approach is introduced here for B-splines. An example shows that, besides great computational complexity savings, this approach obtains better results than the standard, discrete technique, as the performance surface employed is more similar to the one obtained with the function underlying the data. In some cases, as shown in the example, a complete analytical solution can be found. © 2012 IFAC.

Open Access: Yes

DOI: 10.3182/20120403-3-DE-3010.00070

The possible applications of Fuzzy logic for the treatment of conflicts in the dispositional tasks of railway traffic control centers

Tibor Héray Gábor Rózsa L. T. Koczy

Publication Name: IEEE AFRICON Conference

Publication Date: 2007-12-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

the handling of traffic conflicts of trains is rather complicated if full dynamic models are used. Often it is senseless to take into consideration all details of the motion equations and environmental parameters especially as the main parameters, like maximum speed of the trains involved are not exactly known. Also, a large number of noise type variables are always available. The paper proposes the use of the Mamdani type fuzzy rule based reasoning algorithm for handling railway traffic conflicts. The essential point is the granulation of all important parameters into a relatively small number of categories labeled by terms such as small, large, etc. This way the possible decisions for a concrete traffic conflict situation get various fuzzy weights after accumulation of all the fired rules. The final (non-fuzzy) decision is taken by choosing the option with the largest weight. A simplified example is presented for a delay and overtaking type conflict. ©2007 IEEE.

Open Access: Yes

DOI: 10.1109/AFRCON.2007.4401624

Using multiple populations of memetic algorithms for fuzzy rule-base optimization

Krisztián Balázs Zsolt Dányádi L. T. Koczy

Publication Name: 11th IEEE International Symposium on Computational Intelligence and Informatics Cinti 2010 Proceedings

Publication Date: 2010-12-01

Volume: Unknown

Issue: Unknown

Page Range: 113-118

Description:

Evolutionary algorithms are an important branch of soft computing, being able to provide approximate solutions to problems in a reasonable amount of time. The underlying principle can be realized in an almost unlimited number of ways. This paper presents four main variants of evolutionary algorithms, and a method of running them in a topology consisting of multiple populations. The resources given to each population and migration are altered dynamically throughout the test, based on the effectiveness they show. Along with evolutionary methods, the solutions are also adjusted by gradient-based numerical optimization, in our case the Levenberg-Marquardt algorithm. These steps are added to the evolutionary processes as an extension, resulting in what are called memetic algorithms. The specific application for these methods here is optimizing fuzzy rule-bases, thereby making inference systems better at emulating a desired behavior, such as modeling a certain objective function. ©2010 IEEE.

Open Access: Yes

DOI: 10.1109/CINTI.2010.5672264

Historical origin of the fine structure constant subtilis structurae constan unit s1 part i. St. Stephen's crowning achievement

P. Várlaki L. T. Koczy I. J. Rudas

Publication Name: Acta Polytechnica Hungarica

Publication Date: 2010-05-31

Volume: 7

Issue: 1

Page Range: 119-157

Description:

This paper deals with the historical origin of the primordial image of the fine structure constant (FSC) and the number 137 as the Self's own number archetype, which plays a central role in the poetic-hermeneutic system of the Holy Crown of Hungary. We intend to show that the allegorical and symbolical images which are observed as the manifestation of unconscious and interpreted and analyzed in the Pauli-Jung collaboration have a lengthy synchronistic relationship with the "archetypal model" of the FSC found in the marvellous enamel pictures of St. Stephen's Crown.

Open Access: Yes

DOI: DOI not available

On the issue of learning weights from observations for fuzzy signatures

B. Sumudu U. Mendis T. D. Gedeon L. T. Koczy

Publication Name: 2006 World Automation Congress Wac 06

Publication Date: 2006-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

We investigate the issue of obtaining weights, which are associated with aggregation in fuzzy signatures, from real world data, Our approach will provide a way to extract the relevance of lower levels to the higher levels of the hierarchical fuzzy signature structure. We also handle the non-differentiability of max-min aggregation functions for gradient based learning. A mathematically proved method, which is found in the literature to approximate the derivatives of max-min functions, has been used. Copyright - World Automation Congress (WAC) 2006.

Open Access: Yes

DOI: 10.1109/WAC.2006.376058

Comparative investigation of various evolutionary and memetic algorithms

J. Botzheim Krisztián Balázs L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2010-11-03

Volume: 313

Issue: Unknown

Page Range: 129-140

Description:

Optimization methods known from the literature include gradient techniques and evolutionary algorithms. The main idea of gradient methods is to calculate the gradient of the objective function at the actual point and then to step towards better values according to this value. Evolutionary algorithms imitate a simplified abstract model of evolution observed in nature. Memetic algorithms traditionally combine evolutionary and gradient techniques to exploit the advantages of both methods. Our current research aims to discover the properties, especially the efficiency (i.e. the speed of convergence) of particular evolutionary and memetic algorithms. For this purpose the techniques are compared on several numerical optimization benchmark functions and on machine learning problems. © 2010 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-642-15220-7_11

Sensitivity analysis of the weighted generalized mean aggregation operator and its application to fuzzy signatures

Ádám Bukovics István Harmati L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2014-09-04

Volume: Unknown

Issue: Unknown

Page Range: 1327-1332

Description:

In this paper we give bounds on the changing of the weighted generalized mean in terms of vector norms of the changing of the variables. Applying this result we characterize the sensitivity of fuzzy signatures which equipped with weighted generalized mean operators in their nodes. Finally, a practical example from civil engineering is also examined.

Open Access: Yes

DOI: 10.1109/FUZZ-IEEE.2014.6891814

A new domain decomposition for B-spline neural networks

C. Cabrita A. E. Ruano L. T. Koczy

Publication Name: Proceedings of the International Joint Conference on Neural Networks

Publication Date: 2010-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

B-spline Neural Networks (BSNNs) belong to the class of networks termed grid or lattice-based associative memories networks (AMN). The grid is a key feature since it allows these networks to exhibit relevant properties which make them efficient in solving problems namely, functional approximation, non-linear system identification, and on-line control. The main problem associated with BSNNs is that the model complexity grows exponentially with the number of input variables. To tackle this drawback, different authors developed heuristics for functional decomposition, such as the ASMOD algorithm or evolutionary approaches [2]. In this paper, we present a complementary approach, by allowing the properties of B-spline models to be achieved by non-full grids. This approach can be applied either to a single model or to an ASMOD decomposition. Simulation results show that comparable results, in terms of approximations can be obtained with less complex models. © 2010 IEEE.

Open Access: Yes

DOI: 10.1109/IJCNN.2010.5596648

Fuzziness and computational intelligence: Dealing with complexity and accuracy

L. T. Koczy

Publication Name: Soft Computing

Publication Date: 2006-01-01

Volume: 10

Issue: 2

Page Range: 178-184

Description:

No description provided

Open Access: Yes

DOI: 10.1007/s00500-005-0470-3

Generalised weighted relevance aggregation operators for hierarchical fuzzy signatures

J. Botzheim B. Sumudu U. Mendis T. D. Gedeon L. T. Koczy

Publication Name: Cimca 2006 International Conference on Computational Intelligence for Modelling Control and Automation Jointly with Iawtic 2006 International Conference on Intelligent Agents Web Technologies

Publication Date: 2006-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Hierarchical Fuzzy Signatures are generalizations of the Vector Valued Fuzzy Set concept introduced in the 1970s. A crucial question in the Fuzzy Signature context is what kinds of aggregations are applicable for combining data with partly different substructures. Our earlier work introduced the Weighted Relevance Aggregation method to enhance the accuracy of the final results of calculations based on Hierarchical Fuzzy Signature Structures. In this paper, we further generalise the weights and the aggregation into a new operator called Weighted Relevance Aggregation Operator (WRAO). WRAO enhances the adaptability of the fuzzy signature model to different applications and simplifies the learning of fuzzy signature models from data. We also show the methodology of learning these aggregation operators from data. © 2006 IEEE.

Open Access: Yes

DOI: 10.1109/CIMCA.2006.110

Fuzzy rule base model identification by bacterial memetic algorithms

J. Botzheim László Gál L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2009-09-03

Volume: 222

Issue: Unknown

Page Range: 21-43

Description:

Fuzzy systems have been successfully used in the area of controllers for a long time. The Mamdani method is one of the most popular inference systems for practical applications. The main problem of Mamdani-type inference system and other fuzzy logic based controllers is how to gain the fuzzy rules the inference system based on. Several approaches have been proposed for automatic rule base identification. The bacterial type evolutionary algorithms have been successfully applied for solving this task. These algorithms are based on the Pseudo-Bacterial Genetic Algorithm and are supplied with operations and methods (e.g. the Levenberg-Marquardt method) to complete their task more efficiently. The goal is to create more accurate fuzzy rule bases from input-output data sets as quickly as possible. In this work, we summarize the bacterial type evolutionary algorithms used for fuzzy rule base identification. © 2009 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-642-02187-9_3

Multilayer perceptron implemented by fuzzy flip-flops

László Gál Rita Lovassy L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2008-11-07

Volume: Unknown

Issue: Unknown

Page Range: 1683-1688

Description:

The paper introduces a novel method for constructing Multilayer Perceptron (MLP) Neural Networks (NN) with the aid of fuzzy systems, particularly by deploying fuzzy J-K flip-flops as neurons. The next state Q(t+1) of the J-K fuzzy flip-flops (F³) in terms of input J can be characterized by a more or less S-shaped function, for each F³ derived from the Yager, Dombi, and Fodor norms and co-norms. In this approach, J represents the neuron input. The other input K is wired to the complemental output (K=1-Q), thus an elementary fuzzy sequential unit with a single input and a single output is received. The algebraic F³ having linear J-Q(t+1) characteristics is added to the above three. The paper proposes the investigation of the possibility of constructing multilayer perceptrons from such real fuzzy hardware units. Each of the four candidates for F³-based neurons is examined for its training capability by evaluating and comparing the approximation capabilities for two different transcendental functions. Simulation results are presented. © 2008 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2008.4630597

Fuzzy search space for correction of cognitive biases in constructing mathematical models

P. Földesi Zsolt Dányádi L. T. Koczy

Publication Name: 3rd IEEE International Conference on Cognitive Infocommunications Coginfocom 2012 Proceedings

Publication Date: 2012-12-01

Volume: Unknown

Issue: Unknown

Page Range: 585-589

Description:

In optimization the constructed mathematical models are very often idealized mappings of the actual problem. Considering human decision-making processes there is always a chance that cognitive biases occur when constructing the objective function and the constrains. Misrepresented human desires in the objective function or in the constrains result non-acceptable outcome for the decision-maker. To solve the problem of uncertainty concerning the search space we propose the use of fuzzy search space. Bacterial evolutionary algorithm is applied to demonstrate the difference between solutions with altering degree of satisfaction of the original constrains. By presenting the whole set of solutions to the human decision-maker the cognitive biases encoded into the mathematical model can be corrected. © 2012 IEEE.

Open Access: Yes

DOI: 10.1109/CogInfoCom.2012.6422047

Developing fuzzy cognitive maps for modeling regional waste management systems

R. C. Pozna A. Buruzs L. T. Koczy

Publication Name: Civil Comp Proceedings

Publication Date: 2009-01-01

Volume: 92

Issue: Unknown

Page Range: Unknown

Description:

Sustainable waste management systems necessarily include environmental, economic, social, institutional, legal and technical aspects. As a result of the incompleteness and multiple uncertainties occurring in sustainable waste management systems, we propose the use of fuzzy cognitive maps (FCM) to support the planning and decision making process. It is obvious that uncertainties involved with waste management represent vagueness rather than probability. Fuzzy sets and fuzzy logic are suitable to construct a formal description and a mathematically manageable model of systems and processes with such uncertainties. In the research described in this paper the FCM model of the Gyor RWMS is established and implemented in such a structure that its parameters and weights were flexibly variable. By observation of the model and its time dependent behaviour we determined under what conditions the long-term sustainability of a regional waste management system could be ensured. In this paper, the interpretation of the results obtained by the FCM model for the actual waste management system are presented. © Civil-Comp Press, 2013.

Open Access: Yes

DOI: DOI not available

A Hybrid Discrete Memetic Algorithm for Solving Flow-Shop Scheduling Problems

Olivér Hornyák Károly Nehéz Boldizsar Tuu-Szabo Levente Fazekas L. T. Koczy

Publication Name: Algorithms

Publication Date: 2023-09-01

Volume: 16

Issue: 9

Page Range: Unknown

Description:

Flow-shop scheduling problems are classic examples of multi-resource and multi-operation scheduling problems where the objective is to minimize the makespan. Because of the high complexity and intractability of the problem, apart from some exceptional cases, there are no explicit algorithms for finding the optimal permutation in multi-machine environments. Therefore, different heuristic approaches, including evolutionary and memetic algorithms, are used to obtain the solution—or at least, a close enough approximation of the optimum. This paper proposes a novel approach: a novel combination of two rather efficient such heuristics, the discrete bacterial memetic evolutionary algorithm (DBMEA) proposed earlier by our group, and a conveniently modified heuristics, the Monte Carlo tree method. By their nested combination a new algorithm was obtained: the hybrid discrete bacterial memetic evolutionary algorithm (HDBMEA), which was extensively tested on the Taillard benchmark data set. Our results have been compared against all important other approaches published in the literature, and we found that this novel compound method produces good results overall and, in some cases, even better approximations of the optimum than any of the so far proposed solutions.

Open Access: Yes

DOI: 10.3390/a16090406

Fuzzy flip-flops revisited

Rita Lovassy L. T. Koczy

Publication Name: Advances in Soft Computing

Publication Date: 2007-12-01

Volume: 42

Issue: Unknown

Page Range: 643-652

Description:

J-K flip-flops are elementary digital units providing sequential features/memory functions. Their definitive equation is used both in the minimal disjunctive and conjunctive forms. Fuzzy connectives do not satisfy all Boolean axioms, thus the fuzzy equivalents of these equations result in two non-equivalent definitions, "reset and set type" fuzzy flip-flops (F³) by Hirota & al. when introducing the concept of F³. There are many alternatives for "fuzzifying" digital flip-flops, using standard, algebraic or other connectives. The paper gives an overview of some of the most famous F³-s by presenting their definitions and presenting graphs of the inner state for a typical state value situation. Then a pair of non-associative operators is introduced, and the properties of the respective F³ are discussed. The investigation of possible fuzzy flip-flops is continued by examining Türksen's IVFS, its midpoint values, and by introducing "minimized IVFS" (MIVFS), along with the MIVFS midpoints. © 2007 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-540-72434-6_65

Genetic and bacterial memetic programming approaches in hierarchical-interpolative fuzzy system construction

Krisztián Balázs L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2012-10-23

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

As a straightforward continuation of our previous work in this paper new memetic (combined evolutionary and gradient based) methods are proposed for constructing hierarchical-interpolative fuzzy rule bases in the frame of a supervised machine learning system modeling black box systems defined by input-output pairs. In this work the resulting hierarchical rule bases are constructed by using structure building Genetic and Bacterial Memetic Programming Algorithms, thus stochastic evolutionary optimization methods containing deterministic local search steps. Applying hierarchical-interpolative fuzzy rule bases has proved an efficient way of reducing the complexity of knowledge bases, whereas memetic techniques often ensure a relatively fast convergence in the learning process. The literature has highlighted the advantages of memetic methods against pure evolutionary algorithms, thus the combination of hierarchical-interpolative fuzzy rule bases with memetic techniques may form promising hierarchical-interpolative machine learning systems. © 2012 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZ-IEEE.2012.6251218

Hybrid Bacterial Iterated Greedy heuristics for the Permutation Flow Shop Problem

Krisztián Balázs L. T. Koczy Zoltán Horváth

Publication Name: 2012 IEEE Congress on Evolutionary Computation CEC 2012

Publication Date: 2012-10-04

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

This paper proposes approaches for combining the Iterated Greedy (IG) technique, as a presently state-of-the-art method, with a recently proposed adapted version of the Bacterial Evolutionary Algorithm (BEA) in order to efficiently solve the Permutation Flow Shop Problem. The obtained techniques are evaluated via simulation runs carried out on the well-known Taillard's benchmark problem set. Based on the experimental results the hybrid methods are compared to each other and to the original techniques (i.e. to the original IG and BEA algorithms). © 2012 IEEE.

Open Access: Yes

DOI: 10.1109/CEC.2012.6256167

Learning generalized weighted relevance aggregation operators using levenberg-marquardt method

B. Sumudu U. Mendis T. D. Gedeon L. T. Koczy

Publication Name: Proceedings Sixth International Conference on Hybrid Intelligent Systems and Fourth Conference on Neuro Computing and Evolving Intelligence His Ncei 2006

Publication Date: 2006-12-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

We previously introduced the generalized Weighted Relevance Aggregation Operators (WRAO) for hierarchical fuzzy signatures. WRAO enhances the ability of the fuzzy signature model to adapt to different applications and simplifies the learning of fuzzy signature models from data. In this paper we overcome the practical issues which occur when learning WRAO from data. This paper discuss an algorithm for learning WRAO using the Levenberg-Marquardt (LM) method, which is one of the most sophisticated and widely used gradient based optimization method. Also, this paper shows the successful results of applying the proposed algorithm to extract WRAO for two real world problems namely High Salary Selection and SARS Patient Classification. © 2006 IEEE.

Open Access: Yes

DOI: 10.1109/HIS.2006.264917

Signatures: Definitions, operators and applications to fuzzy modelling

R. C. Pozna Á Ballagi Nicuşor Minculete Radu Emil Precup L. T. Koczy

Publication Name: Fuzzy Sets and Systems

Publication Date: 2012-08-16

Volume: 201

Issue: Unknown

Page Range: 86-104

Description:

This paper presents a new framework for the symbolic representation of data which is referred to as signatures. The definitions of signatures and of signature trees are first given. Original operators on signatures are next presented, i.e., contraction, extension, pruning, addition, multiplication, and grafting. Attractive applications of signatures related to the modelling of fuzzy inference systems are suggested and discussed. An example is included to accompany the theoretical results. © 2012 Elsevier B.V. All rights reserved.

Open Access: Yes

DOI: 10.1016/j.fss.2011.12.016

Fuzzy models and interpolation

J. Botzheim T. D. Gedeon L. T. Koczy

Publication Name: Studies in Fuzziness and Soft Computing

Publication Date: 2007-10-08

Volume: 217

Issue: Unknown

Page Range: 111-131

Description:

This paper focuses on two essential topics of the fuzzy area. The first is the reduction of fuzzy rule bases. The classical inference methods of fuzzy systems deal with dense rule bases where the universe of discourse is fully covered. By applying sparse or hierarchical rule bases the computational complexity can be decreased. The second subject of the paper is the introduction of some fuzzy rule base identification techniques. In some cases the fuzzy rule base might be given by a human expert, but usually there are only numerical patterns available and an automatic method has to be applied to determine the fuzzy rules. © 2007 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-540-73182-5_6

Mamdani-type inference in fuzzy signature based rule bases

Katalin Tamás L. T. Koczy

Publication Name: 8th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics Cinti 2007

Publication Date: 2007-12-01

Volume: Unknown

Issue: Unknown

Page Range: 513-525

Description:

The concept of fuzzy signatures might be useful when modeling complex, well structured problems, where one or several components of the structure are determined at a higher level by a sub-tree of other components. The data set belonging to the problem has an arbitrary structure, from which the structure of the data may slightly differ. An aggregation operator is given for each node, for the purpose of modifying the structure, so that data with missing components can be evaluated. Deducing a conclusion from an observation having such a structure is a key issue. In this paper fuzzy signature based rule bases will be introduced, then the generalisation of the well known Mamdani method for signature based rules will be shown step-by-step. Finally, an example of inference on fuzzy signatures will be discussed.

Open Access: Yes

DOI: DOI not available

Strategic decision support in waste management systems by state reduction in FCM models

F. Hatwágner P. Földesi A. Buruzs L. T. Koczy

Publication Name: Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

Publication Date: 2014-01-01

Volume: 8836

Issue: Unknown

Page Range: 447-457

Description:

In this paper, we introduce a new design for modeling sustainable waste management systems. By its complexity, this model is much more precise in describing the real systems than those found in the relevant literature. We set up a model with six factors and then decomposed the constituting factors up to around thirty subcomponents, thereby established an extremely complex and completely novel model of the Integrated Waste Management System (IWMS) using the system-of-system (SoS) approach with the help of experts. After the investigation of the basic and detailed model and their connection matrices, the following idea arises. The two models differ conceptually and so greatly that less than thirty-three factors should be enough to approximately describe the mechanism of action of the real IWMS. In the following, a new state reduction method is proposed. It can be considered as a generalization of the state reduction procedure of sequential systems and finite state machines. The essence of the proposal is to create clusters of factors and to build a new model using these clusters as factors. This way the number of factors can be decreased to make the model easier to understand and use. Our main goal with this method is to support the strategic decision making process of the stakeholder in order to ensure the long-term sustainability of IWMS.

Open Access: Yes

DOI: 10.1007/978-3-319-12643-2_55

Hierarchical-interpolative fuzzy system construction by Genetic and Bacterial Programming Algorithms

Krisztián Balázs L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2011-09-27

Volume: Unknown

Issue: Unknown

Page Range: 2116-2122

Description:

In this paper a method is proposed for constructing hierarchical- interpolative fuzzy rule bases in order to model black box systems defined by input-output pairs, i.e. to solve supervised machine learning problems. The resulting hierarchical rule base is the knowledge base, which is constructed by using evolutionary techniques, namely, Genetic and Bacterial Programming Algorithms. Applying hierarchical-interpolative fuzzy rule bases is an advanced way of reducing the complexity of the knowledge base, whereas evolutionary methods ensure a relatively efficient learning process. This is the reason of the investigation of this combination. © 2011 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2011.6007594

Generalization capability of neural networks based on fuzzy operators

László Gál Rita Lovassy L. T. Koczy

Publication Name: Applied and Computational Mathematics

Publication Date: 2011-01-01

Volume: 10

Issue: 2

Page Range: 340-355

Description:

This paper discusses the generalization capability of neural networks based on various fuzzy operators introduced earlier by the authors as Fuzzy Flip-Flop based Neural Networks (FNNs), in comparison with standard (e.g. tansig function based, MATLAB Neural Network Toolbox type) networks in the frame of simple function approximation problems. Various fuzzy neurons, one of them based on a pair of new fuzzy intersection and union, and several other selected well known fuzzy operators (£ukasiewicz and Dombi operators) combined with standard negation have been proposed as suitable for the construction of novel FNNs. We briefly present the sigmoid function generators derived from fuzzy J-K and D flip-flops. An advantage of such FNNs is their easy hardware implementability. The experimental results show that these FNNs provide rather good generalization performance, with far better mathematical stability than the standard tansig based neural networks and are more suitable to avoid overfitting in the case of test data containing noisy items in the form of outliers.

Open Access: Yes

DOI: DOI not available

Multi-robot cooperation by fuzzy signature sets

Á Ballagi L. T. Koczy

Publication Name: Imcic 2010 International Multi Conference on Complexity Informatics and Cybernetics Proceedings

Publication Date: 2010-01-01

Volume: 2

Issue: Unknown

Page Range: 154-159

Description:

This paper presents a novel method for control cooperating robots without any explicit communication line. Fuzzy signatures are used as complex state description method for intention guessing and action selection. Finally a possible cooperative robot application on a realistic example with missing data components will be shown.

Open Access: Yes

DOI: DOI not available

Fuzzy signature based fuzzy communication of mobile robots

R. C. Pozna Á Ballagi L. T. Koczy

Publication Name: 2010 IEEE Rivf International Conference on Computing and Communication Technologies Research Innovation and Vision for the Future Rivf 2010

Publication Date: 2010-12-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

This paper presents a novel method for control cooperating robots where the explicit communication line is substituted with fuzzy communication algorithms. Fuzzy signatures are used in a context dependent codebook, as complex state description method for intention guessing and action selection. Finally a possible cooperative robot application on a realistic example with missing data components will be shown. ©2010 IEEE.

Open Access: Yes

DOI: 10.1109/RIVF.2010.5633066

Robustness of fuzzy flip-flop based neural networks

László Gál Rita Lovassy L. T. Koczy

Publication Name: 11th IEEE International Symposium on Computational Intelligence and Informatics Cinti 2010 Proceedings

Publication Date: 2010-12-01

Volume: Unknown

Issue: Unknown

Page Range: 207-211

Description:

In this paper the robustness of three different types of Fuzzy Flip-Flop based Neural Network (FNN) and the standard tansig based neural networks is compared from the various test function approximation goodness points of view. It is tested how well the fuzzy flip-flop based and the simulated neural networks handle the test data sets outlier points. The robust design of the FNN is presented, and the best suitable fuzzy neuron type is emphasized. Furthermore, the sensitivity of fuzzy neural networks to the fuzzy neuron type and hidden layers neuron number is evaluated. ©2010 IEEE.

Open Access: Yes

DOI: 10.1109/CINTI.2010.5672248

Three step bacterial memetic algorithm

László Gál Rita Lovassy L. T. Koczy

Publication Name: Ines 2010 14th International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2010-07-26

Volume: Unknown

Issue: Unknown

Page Range: 31-36

Description:

In order to study the function approximation performance of Fuzzy Neural Networks built up from fuzzy J-K flip-flop neurons a new learning algorithm, the Three Step Bacterial Memetic Algorithm is proposed. Hybrid evolutionary methods that combine genetic type algorithms with "classic" local search have been applied to perform efficient global search. This novel version of the Bacterial Memetic Algorithm with Modified Operator Execution Order (BMAM) is a recently developed technique of hybrid type. This particular merger of evolutionary and gradient based algorithms combining both global and local search consists of bacterial mutation and, as a second step, the Levenberg-Marquardt (LM) method applied for each clone. This LM step saves in this way some potential solutions that could be lost otherwise after each mutation step. As a third step the LM algorithm is recalled for a few iterations for each individual of the population towards reaching the local optimum. In our novel algorithm various kinds of fast algorithm with less complexity, like Quasi-Newton algorithm, Conjugate Gradient algorithm, and two Backpropagation training algorithms: Gradient Descent and Gradient Descent with Adaptive Learning Rate and Momentum are nested in the bacterial mutation. © 2010 IEEE.

Open Access: Yes

DOI: 10.1109/INES.2010.5483817

Fuzzy communication and motion control by fuzzy signatures in intelligent mobile robots

T. D. Gedeon Á Ballagi L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2009-10-26

Volume: 241

Issue: Unknown

Page Range: 147-164

Description:

This paper presents two examples for the deployment of fuzzy signatures in the field of intelligent mobile robots. The first shows a complex lateral drift control method base on fuzzy signatures. This method considers the motion system of the robot as a whole, unlike as simple parts of a complex system. The state space is written down by fuzzy signatures which add up flexibility, adaptability and learning ability to the system. In the second experiment a new communication approach is investigated for intelligent cooperation of autonomous mobile robots. Effective, fast and compact communication is one of the most important cornerstones of a high-end cooperating system. In this paper we propose a fuzzy communication system where the codebooks are built up by fuzzy signatures. We use cooperating autonomous mobile robots to solve some logistic problems. © 2009 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-642-03633-0_9

A comparative study of various evolutionary algorithms used for fuzzy rule-based inference and learning systems

Krisztián Balázs Zsolt Dányádi L. T. Koczy

Publication Name: Iccc Conti 2010 IEEE International Joint Conferences on Computational Cybernetics and Technical Informatics Proceedings

Publication Date: 2010-08-06

Volume: Unknown

Issue: Unknown

Page Range: 49-54

Description:

The goal of this paper is to provide an overview of a variety of evolutionary algorithms, comparing their efficiency on fuzzy rule-based inference and learning. Fuzzy rule-based inference can be used to model a desirable outward behavior of a system when given a specific input, which, in the case of this comparative study, is determined by a set of samples, generated by sufficiently complex objective functions. Optimizing a fuzzy rule-based inference system is a matter of finding a rule base that is as close to imitating the desired behavior as possible. While the specific applications of evolutionary methods are endless, the objective functions used here remain general in nature. © 2010 IEEE.

Open Access: Yes

DOI: 10.1109/ICCCYB.2010.5491228

On using fuzzy c-means clustering in the fuzzy signature concept classification of liver lesions

Ferenc Lilik Melinda Kovacs L. T. Koczy Szilvia Nagy

Publication Name: International Conference on Electrical Computer Communications and Mechatronics Engineering Iceccme 2022

Publication Date: 2022-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Liver is a very unique organ, it has double blood supply, not only through the arteries, but also through the veins. This property makes the contrast material enhanced computer tomography images show very characteristic behavior, depending on the time passed from the adjustment of the contrast material. When diagnosing a nodule in the liver by computer tomography, radiologist experts use multiple images with different delay factors, and generally, five basic characteristic properties of the nodule compared to the normal liver tissues. In the following considerations, we give a simplified model that reproduces the way medical experts take decisions, and offer a possibility to develop a computer aided diagnosis method. The classification of the nodules applies a model with fuzzy signatures, where the aggregation functions in the intermediate nodes are representing the radiologist point of view, while the membership degrees/functions at the leaves of the fuzzy signature's rooted tree are obtained from calculations applying the fuzzy c-means clustering algorithm.

Open Access: Yes

DOI: 10.1109/ICECCME55909.2022.9988684

Fuzzy rule extraction by bacterial memetic algorithms

J. Botzheim C. Cabrita A. E. Ruano L. T. Koczy

Publication Name: International Journal of Intelligent Systems

Publication Date: 2009-03-01

Volume: 24

Issue: 3

Page Range: 312-339

Description:

In our previous papers, fuzzy model identification methods were discussed. The bacterial evolutionary algorithm for extracting fuzzy rule base from a training set was presented. The Levenberg-Marquardt method was also proposed for determining membership functions in fuzzy systems. The combination of the evolutionary and the gradient-based learning techniques is usually called memetic algorithm. In this paper, a new kind of memetic algorithm, the bacterial memetic algorithm., is introduced for fuzzy rule extraction. The paper presents how the bacterial evolutionary algorithm can be improved with the Levenberg-Marquardt technique. © 2009 Wiley Periodicals, Inc.

Open Access: Yes

DOI: 10.1002/int.20338

Comparison of fuzzy rule-based learning and inference systems

J. Botzheim Krisztián Balázs L. T. Koczy

Publication Name: 9th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics Cinti 2008

Publication Date: 2008-12-01

Volume: Unknown

Issue: Unknown

Page Range: 61-75

Description:

In our work we have compared various fuzzy rule based learning and inference systems. The base of the investigations was a modular system that we have implemented in C language. It contains several alternative versions of the two key elements of rule based learning - namely, the optimization algorithm and the inference method - which can be found in the literature. We obtained very different properties when combining these alternatives (changing the modules and connecting them) in all possible ways. The investigations determined the values of the quality measures (complexity and accuracy) of the obtained alternatives both analitically and experimentally where it was possible. Based on these quality measures the combinations have been ordered according to different aspects.

Open Access: Yes

DOI: DOI not available

CONDITION ASSESSMENT OF SIDE CORRIDORS WITH THE USE OF AGGREGATIONS BASED ON FUZZY INFERENCE METHOD

Ádám Bukovics Ferenc Lilik Mate Liszi L. T. Koczy

Publication Name: Rehabend

Publication Date: 2022-01-01

Volume: Unknown

Issue: Unknown

Page Range: 864-872

Description:

Professional maintenance of the residential building stock and completion of the necessary renovation works on time will increase the life of the residential buildings and improve their condition. For this reason, it is important to create and apply condition assessment and decision support systems that uniformly and accurately determine the condition of individual building structures and buildings. Thus, the necessary interventions -taking into account the available financial resources-can be performed at the right time and in the right way. The ultimate goal of our research is to develop a decision support system that evaluates the damage of individual structural members and determines the condition of each load bearing structure, ultimately evaluating the entire building. It then suggests (if necessary) which of the available renovation methods to choose. In addition to the damage of the load bearing structures, the decision among the proposed methods of reinforcement is also influenced by architectural requirements and economic aspects. In the present phase of the research we have developed a method that determines the condition of side corridor structures based on the observed damage detected by visual building diagnostics (e.g. steel cantilever corrosion, stone plate cracks, stone plate abrasion). The side corridors are divided into three well-separable structural elements (cantilever, plate, balustrade) and their damage is analyzed separately. Qualification is made by a fuzzy signature based decision making system. In this, aggregations are based on classical fuzzy inference methods. The rule bases of the aggregation were constructed during this research. The final condition of the side corridor structure is affected by the combined condition of the three structural elements.

Open Access: Yes

DOI: DOI not available

Application of Fuzzy Theory to Investigate the Effect of Innovation Power in the Emergence of an Advanced Reusable Packaging System

Ádám Bukovics P. Földesi A. Buruzs Péter Böröcz L. T. Koczy

Publication Name: Fuzzy Systems Modeling in Environmental and Health Risk Assessment

Publication Date: 2023-01-01

Volume: Unknown

Issue: Unknown

Page Range: 299-307

Description:

In this chapter, the authors present a novel technique to analyze the role of subjective factors such as innovations in the economy that influence the design of reusable packaging systems in a given industrial region. The focus of this chapter is on the power of innovation, which is not a directly measurable unit. Nowadays, with modern supply chains, companies and packaging engineers have to determine what constitutes adequate packaging with optimal waste. These decisions are usually based on known data and information, but the goal now is to create packaging that has a more favorable environmental impact than before. It seems obvious that more advanced regions will create more advanced packaging systems, but either way having an innovative milieu is a necessary prerequisite of this. This chapter shows that a willingness to innovate is an indispensable requirement of the design of advanced packaging and that most of the time this depends on the synergic effect of local production factors and regional peculiarities.

Open Access: Yes

DOI: 10.1002/9781119569503.ch16

Fuzzy flip-flop based neural network as a function approximator

László Gál Rita Lovassy L. T. Koczy

Publication Name: Cimsa 2008 IEEE Conference on Computational Intelligence for Measurement Systems and Applications Proceedings

Publication Date: 2008-09-26

Volume: Unknown

Issue: Unknown

Page Range: 44-49

Description:

Artificial neural networks and fuzzy logic systems, in the context of approximate reasoning, share common features and techniques. A family of fuzzy flip-flops is proposed, based on an artificial neural network-like structure which is suitable for approximating many-input one-output nonlinear functions. The neurons in the multilayer perceptron networks typically employ sigmoidal activation functions. The next state of the fuzzy J-K flip-flops (F³) using Yager and Dombi operators present quasi-S-shaped characteristics. The paper proposes the investigation of the possibility of constructing multilayer perceptrons from such fuzzy units. Each of the two candidates for F ³-based neurons is examined for its training capability by evaluating and comparing the approximation properties in the context of different transcendental functions with one-input and multi-input cases. Simulation results are presented. ©2008 IEEE.

Open Access: Yes

DOI: 10.1109/CIMSA.2008.4595830

Experimenting with a new population-based optimization technique: FUNgal growth inspired (FUNGI) optimizer

Alex Tormási L. T. Koczy

Publication Name: Studies in Fuzziness and Soft Computing

Publication Date: 2018-01-01

Volume: 361

Issue: Unknown

Page Range: 123-135

Description:

In this paper the experimental results of a new evolutionary algorithm are presented. The proposed method was inspired by the growth and reproduction of fungi. Experiments were executed and evaluated on discretized versions of common functions, which are used in benchmark tests of optimization techniques. The results were compared with other optimization algorithms and the directions of future research with many possible modifications/extension of the presented method are discussed.

Open Access: Yes

DOI: 10.1007/978-3-319-75408-6_11

Fuzzy solution for non-linear quality models

J. Botzheim P. Földesi L. T. Koczy

Publication Name: 12th International Conference on Intelligent Engineering Systems Proceedings Ines 2008

Publication Date: 2008-09-01

Volume: Unknown

Issue: Unknown

Page Range: 269-275

Description:

For designing and developing products/services it is vital to know the relevancy of the performance generated by each technical attribute and how they can increase customer satisfaction. Improving the parameters of technical attributes requires financial resources, and the budgets are generally limited. Thus the optimum target is to achieve maximum customer satisfaction within given financial limits. Kano's quality model classifies the relationships between customer satisfaction and attribute-level performance and indicates that some of the attributes have a non-linear relationship to satisfaction, rather power-function should be used. For the customers' subjective evaluation these relationships are not deterministic and are uncertain. This paper proposes a method for fuzzy extension of Kano's model and presents numerical examples that can prove the efficiency of bacterial evolutionary algorithm in as well. © 2008 IEEE.

Open Access: Yes

DOI: 10.1109/INES.2008.4481306

Fuzzy signature based mobil robot motion control system

Á Ballagi L. T. Koczy

Publication Name: Sami 2008 6th International Symposium on Applied Machine Intelligence and Informatics Proceedings

Publication Date: 2008-08-25

Volume: Unknown

Issue: Unknown

Page Range: 29-33

Description:

The differentially steered drive system used in many robots is essentially the same arrangement as that used in a wheelchair. Thus, steering the robot is just a matter of varying the speeds of the drive wheels. At least two independent driving chain are used in most of differentially steered drive system. Each driver wheel has the own controller in a traditional motion system, which give a hard tuned, rigid arrangement. In this paper we propose a complex lateral drift control method base on fuzzy signatures. This method inspects the motion system as a whole, unlike as simple parts of a complex system. The state space is written down by fuzzy signatures which adds up flexibility, adaptability and learning ability to system. © 2008 IEEE.

Open Access: Yes

DOI: 10.1109/SAMI.2008.4469193

Fuzzy rule base extraction by the improved bacterial memetic algorithm

J. Botzheim László Gál A. E. Ruano L. T. Koczy

Publication Name: Sami 2008 6th International Symposium on Applied Machine Intelligence and Informatics Proceedings

Publication Date: 2008-08-25

Volume: Unknown

Issue: Unknown

Page Range: 49-53

Description:

In this paper we introduce new methods for handling knot order violation occurred in the Bacterial Memetic Algorithm (BMA) used for fuzzy rule base extraction. These methods perform slightly better than the method used before and are easier to integrate with the Bacterial Memetic Algorithm. ©2008 IEEE.

Open Access: Yes

DOI: 10.1109/SAMI.2008.4469132

Notes on the Dynamics of Hyperbolic Tangent Fuzzy Cognitive Maps

István Harmati L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2019-06-01

Volume: 2019-June

Issue: Unknown

Page Range: Unknown

Description:

Fuzzy cognitive maps (FCMs) are recurrent neural networks applied for modelling complex systems and structures. In this method, the system is represented by a weighted, directed digraph, where the nodes of the network represent the main characteristics of the modelled system, while the weighted and directed edges correspond to the direction and strength of causal relationships between these factors. The FCM based decision making is based on the so-called activation values of the nodes, which represents the state of the system. These activation values are determined by an iteration, which may lead to an equilibrium point (fixed point), but limit cycles or chaotic behaviour may also occur. In this paper, the dynamics of fuzzy cognitive maps with hyperbolic tangent threshold function is mathematically discussed. Theoretical conditions are provided for the existence and uniqueness of fixed points. Moreover, the stability of fixed points and their basins of attractions are also analysed. The results presented here give insight into the special symmetric nature of hyperbolic FCMs.

Open Access: Yes

DOI: 10.1109/FUZZ-IEEE.2019.8858950

Intelligent Traffic Signal Control Using Rule Based Fuzzy System

Tamrat Delessa Chala L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2023-01-01

Volume: 1087

Issue: Unknown

Page Range: 347-371

Description:

Over the past decades, there has been an ever-increasing saturation of traffic networks due to the growing number of road vehicles, and due to the available limited. To solve these problems, adaptive, (semi-) intelligent traffic control has been used widely for the last decades. These systems nevertheless, have some shortages, the most obvious one being that these systems use the presence of vehicles at the lanes immediately before reaching the intersections. The real queue size cannot be taken into consideration. In the present approach, the input values are supposed to come from cameras connected with image processing systems and directed microphones. We propose a new traffic signal control system with a hierarchical structure based on similarly Mamdani control, however, containing essentially novel elements and having more intelligent features. This new model and the connected algorithmic approach allow rather complex control strategies, but only a simple case study has been implemented. Compared with existing fuzzy traffic controls, the novel approach has more adaptability and flexibility, by having the potential to differentiate an arbitrary number of traffic directions and by increasing general safety by the additional emergency vehicle handling feature. In addition, the calculation with queues, and individual vehicles weighted with the waiting time makes the system more flexible than any existing intelligent model.

Open Access: Yes

DOI: 10.1007/978-3-031-25759-9_17

Fuzzy flip-flops and neural nets?

Rita Lovassy L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2007-12-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

J-K flip-flops are elementary digital units providing sequential features/memory functions. Their definitive equation is used both in the minimal disjunctive and conjunctive forms. Fuzzy connectives do not satisfy all Boolean axioms, thus the fuzzy equivalents of these equations result in two non-equivalent definitions, "reset and set type" fuzzy flip-flops (F³) by Hirota & al. when introducing the concept of F ³. The paper gives an overview of some of the most famous F ³-s by presenting their definitions and graphs. An interesting aspect of F³-s might be that they have a certain convergent behavior when one of their inputs (e.g. J) is exited repeatedly. This is true even if the other input (K) is kept at a constant value. The behavior is more versatile if both inputs are given a series of changing values. If J is considered the equivalent of the traditional input of a neuron (with an adder unit applied before J), K might play a secondary modifier's role, or can just be set fix. The paper encourages to the investigation of such possible F³-networks as new alternative types of neural networks. © 2007 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2007.4295435

Fuzzy extension for Kano's model using bacterial evolutionary algorithm

J. Botzheim P. Földesi L. T. Koczy

Publication Name: Isciii 07 3rd International Symposium on Computational Intelligence and Intelligent Informatics Proceedings

Publication Date: 2007-09-25

Volume: Unknown

Issue: Unknown

Page Range: 147-151

Description:

For designing and developing products/services it is vital to know the relevancy of the performance generated by each technical attribute and how they can increase customer satisfaction. Improving the parameters of technical attributes requires financial resources, and the budgets are generally limited. Thus the optimum target is to achieve maximum customer satisfaction within given financial limits. Kano's quality model classifies the relationships between customer satisfaction and attribute-level performance and indicates that some of the attributes have a nonlinear relationship to satisfaction, rather power-function should be used. For the customers' subjective evaluation these relationships are not deterministic and are uncertain. This paper proposes a method for fuzzy extension of Kano's model and presents numerical examples that can prove the efficiency of bacterial evolutionary algorithm in as well. © 2007 IEEE.

Open Access: Yes

DOI: 10.1109/ISCIII.2007.367379

Experiments with the Discrete Bacterial Memetic Evolutionary Algorithm for Solving the Cumulative Capacitated Vehicle Routing Problem

P. Földesi Boldizsar Tuu-Szabo L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2023-01-01

Volume: 1040

Issue: Unknown

Page Range: 87-92

Description:

In this paper we present our initial experiments with the Discrete Bacterial Memetic Evolutionary Algorithm for solving the Cumulative Capacitated Vehicle Routing Problem. The algorithm was tested on instances proposed in the literature. However our method was able to find the optimal solution for small (around 50 nodes) instances, but its convergence speed is low. In the last section some of our ideas to improve the performance of the algorithm were presented.

Open Access: Yes

DOI: 10.1007/978-3-031-07707-4_11

Fuzzy Inference System-like Aggregation Operator for Fuzzy Signatures

Ádám Bukovics Ferenc Lilik L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2023-01-01

Volume: 1040

Issue: Unknown

Page Range: 93-101

Description:

This paper deals with a novel fuzzy aggregation operator. This aggregation operator is suggested to such fuzzy signatures, where the correlation between the leafs or branches can not be handled by classical operators as weighted relevance aggregation operator or weighted generalized mean, more with fuzzy rules. This paper presents the suggested Fuzzy inference system-like aggregation operator (FISAO), shows its axiomatic conformity and depicts its use through an experimental example.

Open Access: Yes

DOI: 10.1007/978-3-031-07707-4_12

Symmetry or Asymmetry? Complex Problems and Solutions by Computational Intelligence and Soft Computing

L. T. Koczy

Publication Name: Symmetry

Publication Date: 2022-09-01

Volume: 14

Issue: 9

Page Range: Unknown

Description:

No description provided

Open Access: Yes

DOI: 10.3390/sym14091839

Separated antecedent and consequent learning for Takagi-Sugeno fuzzy systems

J. Botzheim T. D. Gedeon Erich Peter Klement Edwin Lughofer L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2006-12-01

Volume: Unknown

Issue: Unknown

Page Range: 2263-2269

Description:

In this paper a new algorithm for the learning of Takagi-Sugeno fuzzy systems is introduced. In the algorithm different learning techniques are applied for the antecedent and the consequent parameters of the fuzzy system. We propose a hybrid method for the antecedent parameters learning based on the combination of the Bacterial Evolutionary Algorithm (BEA) and the Levenberg-Marquardt (LM) method. For the linear parameters in fuzzy systems appearing in the rule consequents the Least Squares (LS) and the Recursive Least Squares (RLS) techniques are applied, which will lead to a global optimal solution of linear parameter vectors in the least squares sense. Therefore a better performance can be guaranteed than with a complete learning by BEA and LM. The paper is concluded by evaluation results based on high-dimensional test data. These evaluation results compare the new method with some conventional fuzzy training methods with respect to approximation accuracy and model complexity. © 2006 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2006.1682014

Fuzzy models, identification and applications

J. Botzheim L. T. Koczy

Publication Name: Iccc 2005 IEEE 3rd International Conference on Computational Cybernetics Proceedings

Publication Date: 2005-12-01

Volume: 2005

Issue: Unknown

Page Range: 13-19

Description:

This paper gives a brief overview of fuzzy model identification techniques. The paper discusses how the membership functions of a fuzzy system can be extracted from an input/output data (pattern) set without human interference. There are several methods used for rule extraction known from the literature. The bacterial algorithm is an evolutionary technique that was inspired by the microbial evolution phenomenon. The Levenberg-Marquardt algorithm is an advanced gradient type optimization method that has been developed initially for neural networks and is introduced here for the optimization of the fuzzy rule base. Fuzzy clustering is presented also as another alternative way for the rule extraction. In the part describing the model the fuzzy rule interpolation method and the approach of hierarchical rule bases are introduced. Combining fuzzy rule interpolation with the use of hierarchically structured fuzzy rule bases leads to the reduction of the fuzzy algorithms' complexity. Hierarchical fuzzy modeling by clustering techniques is also introduced in the paper.

Open Access: Yes

DOI: 10.1109/ICCCYB.2005.1511538

Fuzzy rule interpolation for multidimensional input spaces with applications: A case study

T. D. Gedeon Domonkos Tikk L. T. Koczy Kok Wai Wong

Publication Name: IEEE Transactions on Fuzzy Systems

Publication Date: 2005-12-01

Volume: 13

Issue: 6

Page Range: 809-819

Description:

Fuzzy rule based systems have been very popular in many engineering applications. However, when generating fuzzy rules from the available information, this may result in a sparse fuzzy rule base. Fuzzy rule interpolation techniques have been established to solve the problems encountered in processing sparse fuzzy rule bases. In most engineering applications, the use of more than one input variable is common, however, the majority of the fuzzy rule interpolation techniques only present detailed analysis to one input variable case. This paper investigates characteristics of two selected fuzzy rule interpolation techniques for multidimensional input spaces and proposes an improved fuzzy rule interpolation technique to handle multidimensional input spaces. The three methods are compared by means of application examples in the field of petroleum engineering and mineral processing. The results show that the proposed fuzzy rule interpolation technique for multidimensional input spaces can be used in engineering applications. © 2005 IEEE.

Open Access: Yes

DOI: 10.1109/TFUZZ.2005.859316

A Combined Approach of Fuzzy Cognitive Maps and Fuzzy Rule-Based Inference Supporting Freeway Traffic Control Strategies †

F. Hatwágner Mehran Amini L. T. Koczy

Publication Name: Mathematics

Publication Date: 2022-11-01

Volume: 10

Issue: 21

Page Range: Unknown

Description:

Freeway networks, despite being built to handle the transportation needs of large traffic volumes, have suffered in recent years from an increase in demand that is rarely resolvable through infrastructure improvements. Therefore, the implementation of particular control methods constitutes, in many instances, the only viable solution for enhancing the performance of freeway traffic systems. The topic is fraught with ambiguity, and there is no tool for understanding the entire system mathematically; hence, a fuzzy suggested algorithm seems not just appropriate but essential. In this study, a fuzzy cognitive map-based model and a fuzzy rule-based system are proposed as tools to analyze freeway traffic data with the objective of traffic flow modeling at a macroscopic level in order to address congestion-related issues as the primary goal of the traffic control strategies. In addition to presenting a framework of fuzzy system-based controllers in freeway traffic, the results of this study demonstrated that a fuzzy inference system and fuzzy cognitive maps are capable of congestion level prediction, traffic flow simulation, and scenario analysis, thereby enhancing the performance of the traffic control strategies involving the implementation of ramp management policies, controlling vehicle movement within the freeway by mainstream control, and routing control.

Open Access: Yes

DOI: 10.3390/math10214139

Extension of the Time Dependent Travelling Salesman Problem with Interval Valued Intuitionistic Fuzzy Model Applying Memetic Optimization Algorithm

P. Földesi Boldizsar Tuu-Szabo Ruba Almahasneh L. T. Koczy

Publication Name: ACM International Conference Proceeding Series

Publication Date: 2020-03-21

Volume: Unknown

Issue: Unknown

Page Range: 111-118

Description:

The Time Dependent Traveling Salesman Problem (TD TSP) is an extension of the classic Traveling Salesman Problem towards more realistic conditions. TSP is one of the most extensively studied NP-complete graph search problems. In TD TSP, the edges are assigned different weights, depending on whether they are traveled in the traffic jam regions (such as busy city centers) and during rush hour periods, or not. In such circumstances, edges are assigned higher costs, expressed by a multiplying factor. In this paper, we introduce a novel and even more realistic approach, the Interval Intuitionistic Fuzzy Time Dependent Traveling Salesman Problem (IVIFTD TSP); which is a further extension of the classic TD TSP, with the additional notion of deploying interval valued intuitionistic fuzzy for describing uncertainties. The core concept employs interval valued intuitionistic fuzzy sets for quantifying the traffic jam regions, and the rush hour periods loss (those are additional costs of the travel between nodes), which are always uncertain in real life. Since type-2 (such as inter valued) fuzzy sets have the potential to provide better performance in modeling problems with higher uncertainties than the traditional fuzzy set, the new approach it may be considered as an extended, practically more applicable, extended version of the original abstract problem. The optimization of such a complex model is obviously very difficult; it is a mathematically intractable problem. However, the Discrete Bacterial Memetic Evolutionary Algorithm proposed earlier by the authors' team has shown sufficient efficiency, general applicability for similar type problems and good predictability in terms of problem size, thus it is applied for the optimization of the concrete instances.

Open Access: Yes

DOI: 10.1145/3396474.3396490

Parameterization and concept optimization of FCM models

F. Hatwágner L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2015-11-25

Volume: 2015-November

Issue: Unknown

Page Range: Unknown

Description:

Fuzzy Cognitive Maps (FCM) are widely used to model and analyze the behavior of complex multicomponent systems. The application of FCM might be non-trivial in some specific context, however. Two rather general problems of the application of FCM and respective solutions are described in this paper. The first problem is as follows: In some cases the concept values obtained at the end of an FCM simulation are very similar. If this occurs, the order of concepts, thus their relative importance cannot well defined. The second problem is to select the appropriate concepts and to define their number. The concepts are given by human experts, but the selection of the appropriate concepts which help to reach the required accuracy of the model, while keeping the model as simple as possible is a difficult task. This paper deals with these two (connected) problems and proposes solutions for them. The proposed solution for the first problem is to choose the optimal λ parameter value in the threshold function, the one for the second is to apply a 'state reduction method' based on fuzzy tolerance relations presented in the paper.

Open Access: Yes

DOI: 10.1109/FUZZ-IEEE.2015.7337888

A hybrid discrete bacterial memetic algorithm with simulated annealing for optimization of the flow shop scheduling problem

Olivér Hornyák Károly Nehéz Anita Agárdi L. T. Koczy

Publication Name: Symmetry

Publication Date: 2021-07-01

Volume: 13

Issue: 7

Page Range: Unknown

Description:

This paper deals with the flow shop scheduling problem. To find the optimal solution is an NP-hard problem. The paper reviews some algorithms from the literature and applies a benchmark dataset to evaluate their efficiency. In this research work, the discrete bacterial memetic evolutionary algorithm (DBMEA) as a global searcher was investigated. The proposed algorithm improves the local search by applying the simulated annealing algorithm (SA). This paper presents the experimental results of solving the no-idle flow shop scheduling problem. To compare the proposed algorithm with other researchers’ work, a benchmark problem set was used. The calculated makespan times were compared against the best-known solutions in the literature. The proposed hybrid algorithm has provided better results than methods using genetic algorithm variants, thus it is a major improvement for the memetic algorithm family solving production scheduling problems.

Open Access: Yes

DOI: 10.3390/sym13071131

Criticality analysis of purchased materials based on fuzzy signatures

P. Földesi Gabor Farkas L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2017-08-23

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Selecting and evaluating the suppliers represent a very complex task, because a wide range of attributions must be taken into consideration and many of them are difficult to be made objectively quantified. The aim of this research is to provide a new model based on fuzzy signatures for selecting and evaluating the critical parts for the production.

Open Access: Yes

DOI: 10.1109/FUZZ-IEEE.2017.8015649

Combining fuzzy signature and rough sets approach for predicting the minimum passing level of competency achievement

Siti Rochimah Umi Laili Yuhana Nurul Zainal Fanani Eko Mulyanto Yuniarno Mauridhi Hery Purnomo L. T. Koczy

Publication Name: International Journal of Artificial Intelligence

Publication Date: 2020-03-01

Volume: 18

Issue: 1

Page Range: 237-249

Description:

This paper aims to investigate the important factors that affect the value of the minimum passing level (MPL) of competency achievement and find the best method to predict it. The MPL of competency achievement is the value that represents the minimum passing score of examination related to the competency. Different schools may have a different value of the MPL because the MPL is defined based expert opinion on several uncertainty aspects and conditions at each school. This paper proposes the combination of rough sets and fuzzy signature method to predict the category of the MPL. The rough sets method is applied to reduce unnecessary features for classification and find the important factors to predict the MPL. The fuzzy signature is employed to predict the category of MPL based on the selected features. The method proposed in this paper consists of several stages, namely data collection and pre-processing, features selection, predict the category of the MPL using the combination of rough sets and fuzzy signatures method, and performance evaluation. Fifteen headmasters and sixty teachers of elementary schools participated in the data collection process. Based on the experiment with 203 objects data we achieved 97% accuracy in the prediction of MPL. The proposed method succeeded to identify the important factors on predicting the MPL on the complexity of competency and resource capacity of the school aspect. We obtained the improvement for accuracy of the complexity of competency prediction of 8.5% from the best method in the previous research.

Open Access: Yes

DOI: DOI not available

Three level fuzzy signature based decision methodology for packaging system design

P. Földesi A. Buruzs Kata Vöröskoi Gergő Fogarasi L. T. Koczy

Publication Name: Journal of Automation Mobile Robotics and Intelligent Systems

Publication Date: 2020-01-01

Volume: 14

Issue: 2

Page Range: 99-105

Description:

In the field of logistics packaging, companies have to take decisions on determining the optimal packaging solutions and expenses. The decisions often involve a choice between one-way (disposable) and reusable (returnable) packaging solutions. Even nowadays, in most cases the decisions are made based on traditions and mainly consider the material and investment costs. Although cost is an important factor, it might not be sufficient for finding the optimal solution. Traditional (two-valued) logic is not suitable for modelling this problem, so here the application of a fuzzy approach, because of the metrical aspects, a fuzzy signature approach is considered. In this paper three different fuzzy signatures connected by fuzzy rules modelling the packaging decision are suggested, based on logistics expert opinions, in order to support the decision making process of choosing the right packaging system. Two real life examples are also given, one in the field of customer packaging and one in industrial packaging.

Open Access: Yes

DOI: 10.14313/JAMRIS/2-2020/25

Comparison of Discrete Memetic Evolutionary Metaheuristics for TSP

P. Földesi Boldizsar Tuu-Szabo Gergő Fogarasi L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2022-01-01

Volume: 955

Issue: Unknown

Page Range: 29-37

Description:

In our paper we compare discrete memetic evolutionary metaheuristics (and other algorithms) which are applicable (also) for the widely studied and industrially applied (symmetric, Euclidean) NP-hard combinatorial optimization problem called Traveling Salesman Problem (TSP) such as DBMEA (Discrete Bacterial Memetic Evolutionary Algorithm), DMTLBO (Discrete Memetic Teaching–Learning Based Optimization) not to mention DMSSA (Discrete Memetic Squirrel Search Algorithm) algorithms. The comparisons occurred under the same fixed conditions.

Open Access: Yes

DOI: 10.1007/978-3-030-88817-6_4

Forward and backward fuzzy rule base interpolation using fuzzy geometry

Suman Das L. T. Koczy Debjani Chakraborty

Publication Name: Iranian Journal of Fuzzy Systems

Publication Date: 2023-05-01

Volume: 20

Issue: 3

Page Range: 127-146

Description:

Fuzzy rule interpolation (FRI) predicts an accountable outcome of a possible course of action in sparse fuzzy rule base system (FRBS). The geometry based linear fuzzy rule interpolation (GLFRI) is extended for multi-dimensional fuzzy rule base interpolation. Expansion/contraction (EC) of triangular, trapezoidal and complex polygonal fuzzy sets has been also proposed which enables the proposed FRI method to incorporate with fuzzy rules which include triangular, trapezoidal, hexagonal or complex fuzzy sets. The study further extends to introduce the process of backward rule base interpolation. It has been shown that the scale and move transformation-based FRI method can yield a non-convex fuzzy consequent which can be avoided by using the proposed method. The proposed method performs better without any risk of obtaining non-convex fuzzy consequent. The efficiency of proposed forward and backward FRI methods is projected with several numerical examples. A detailed comparison of EC transformation with scale and move transformation is also presented here.

Open Access: Yes

DOI: 10.22111/ijfs.2023.7643

Local Binary Pattern-Based Fingerprint Matching

P. Földesi Boldizsar Tuu-Szabo Gábor Kovács L. T. Koczy Szilvia Nagy

Publication Name: Studies in Computational Intelligence

Publication Date: 2022-01-01

Volume: 959

Issue: Unknown

Page Range: 183-188

Description:

In this paper we propose an image-based fingerprint recognition system. The method is based on Local Binary Pattern features extracted from the region of the fingerprint image around the core point. The experiments on the FVC2002 fingerprint databases show the effectiveness of the proposed approach.

Open Access: Yes

DOI: 10.1007/978-3-030-74970-5_21

Comparing the properties of meta-heuristic optimization techniques with various parameters on a fuzzy rule-based classifier

Alex Tormási L. T. Koczy

Publication Name: Studies in Fuzziness and Soft Computing

Publication Date: 2016-01-01

Volume: 342

Issue: Unknown

Page Range: 157-169

Description:

In this paper, the results of meta-heuristic optimization techniques with various parameter settings are presented. A formerly published Fuzzy-Based Recognizer (FUBAR): A fuzzy rule-based classification algorithm was used to analyze and evaluate the behavior of the used meta-heuristic optimization algorithms for rule-base optimization. Besides the reached accuracy, the execution time, the CPU load of the algorithms, and the effects of the shapes of the fuzzy membership functions in the initial rule-base are also investigated.

Open Access: Yes

DOI: 10.1007/978-3-319-32229-2_12

Fuzzy System-Based Solutions for Traffic Control in Freeway Networks Toward Sustainable Improvement

F. Hatwágner Mehran Amini L. T. Koczy

Publication Name: Communications in Computer and Information Science

Publication Date: 2022-01-01

Volume: 1602 CCIS

Issue: Unknown

Page Range: 288-305

Description:

In the scientific community, the topic of traffic control for promoting sustainable transportation in freeway networks is a relatively new field of research that is becoming increasingly relevant. Sustainability is a critical factor in the design and operation of mobility and traffic systems, which impacts the development of freeway traffic control strategies. According to sustainable notions, freeway traffic controllers should be designed to maximize road capacity, minimize vehicle travel delays, and reduce pollution emissions, accidents, and fuel consumption. The problem is full of uncertainty, there is no way to model the whole system analytically, thus a fuzzy modeling approach seems to be not only adequate but necessary. In this study, a Fuzzy Cognitive Map based model (FCM) and a connected simple Fuzzy Inference System (FIS) are presented, as the tools to analyze freeway traffic data with the goal of traffic flow modeling at a macroscopic level, in order to address congestion-related issues as the core of the sustainability improvement strategies. Besides presenting a framework of Fuzzy system-based controllers in freeway traffic, the results of this work indicated that FIS and FCM are capable of realizing traffic control strategies involving the implementation of ramp management policies, controlling vehicle movement within the freeway by mainstream control, and routing vehicles along alternative paths via the execution of suitable route guidance strategy.

Open Access: Yes

DOI: 10.1007/978-3-031-08974-9_23

Fuzzy State Machine-Based Refurbishment Protocol for Urban Residential Buildings

G. Molnárka L. T. Koczy

Publication Name: Communications in Computer and Information Science

Publication Date: 2014-01-01

Volume: 443 CCIS

Issue: PART 2

Page Range: 375-384

Description:

The urban-type residential houses built before World War Two represent a large part of the built environment in Hungary. Due to their physical condition and low energy-efficiency the retrofit of these buildings is very much advisable nowadays. In this paper we propose an approach based on fuzzy signatures and state machines, that helps decision support for determining the renovation scenario concerning necessity, cost efficiency and quality. Using the knowledge obtained from diagnostic surveys done during the previous decades by architect experts, and technical guides and the available database of contractors billing, a protocol for the preparation for optimized refurbishment is proposed, based on the concept of an extended fuzzy state machine model. In this combined model the theoretical concepts of finite-state machine and fuzzy state machine, and also the principles of fuzzy signatures are applied. © Springer International Publishing Switzerland 2014.

Open Access: Yes

DOI: 10.1007/978-3-319-08855-6_38

A new efficient tour construction heuristic for the Traveling Salesman Problem

Boldizsar Tuu-Szabo Ali Jawad Ibada L. T. Koczy

Publication Name: ACM International Conference Proceeding Series

Publication Date: 2021-04-10

Volume: Unknown

Issue: Unknown

Page Range: 71-76

Description:

The creation of the initial population is an essential part of the population based evolutionary algorithms. An appropriate initial population could lead to much faster convergence speed; in contrast, an inappropriate initial population could even cause getting stuck in a local optimum. In this paper, we will propose a new efficient heuristic method to create initial individuals for the Traveling Salesman Problem (TSP), which we will call Circle Group Heuristic (CGH). The results show that CGH creates better tours compared with other well-known heuristic tour construction methods.

Open Access: Yes

DOI: 10.1145/3461598.3461610

Fuzzy cognitivemaps and bacterial evolutionary algorithm approach to integratedwaste management systems

F. Hatwágner A. Buruzs L. T. Koczy

Publication Name: Journal of Advanced Computational Intelligence and Intelligent Informatics

Publication Date: 2014-01-01

Volume: 18

Issue: 4

Page Range: 538-548

Description:

Sustainable wastemanagement systems necessarily include many interacting factors. Due to the complexity and uncertainties occurring in sustainable waste management systems, we propose the use of Fuzzy Cognitive Maps (FCM) and Bacterial Evolutionary Algorithm (BEA) [1] to support the planning and decision making process of integrated systems, as the combination of methods FCM and BEA seems to be suitable to model such complex mechanisms as Integrated Waste Management Systems (IWMS). This paper is an attempt to assess the sustainability of the IWMS in a holistic approach. While the FCM model represents the IWMS as a whole, the BEA is used for parameter optimization and identification. An interpretation of the results obtained by the FCMfor the actual regional IWMS is also presented. We have obtained some surprising results, contradicting the general assumptions in the literature concerning the relative importance of constituting components in waste management systems.

Open Access: Yes

DOI: 10.20965/jaciii.2014.p0538

Discrete Bacterial Memetic Evolutionary Algorithms for Solving High Complexity Problems: PLENARY TALK

L. T. Koczy

Publication Name: Saci 2022 IEEE 16th International Symposium on Applied Computational Intelligence and Informatics Proceedings

Publication Date: 2022-01-01

Volume: Unknown

Issue: Unknown

Page Range: 13-14

Description:

In the talk, several examples will be presented with standard benchmarks going up to large numbers of graph nodes, and the DBMEA results will be compared with the best practices from the literature. The predictability feature will also be illustrated by size-running time graphs. Reference will be made to the importance of determining the initial population in achieving fast and accurate results. A new approach, the Bounded Radius Heuristics will be presented. In the last part of the talk, a series of fuzzy extensions of the Time Dependent TSP (TD TSP) will be introduced, an extension of the TSP with real life aspects where the natural fluctuation of the traffic in certain areas causes non-deterministic features causing additional difficulties in the quasi-optimization. The novel extensions will be also tackled with the DBMEA approach successfully. As a conclusion, one more example will be mentioned where the discrete NP-hard problem is of a rther different nature, and it will be shown that by changing the local search technique appropriately, DBMEA can still deliver superior results.

Open Access: Yes

DOI: 10.1109/SACI55618.2022.9919503

Nonlinear systems controller design as a result of uninorm tuning

R. C. Pozna Márta Takács Á Ballagi L. T. Koczy

Publication Name: 2011 2nd International Conference on Cognitive Infocommunications Coginfocom 2011

Publication Date: 2011-09-23

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

The quality of a Fuzzy Logic Controller (FLC) for control nonlinear systems highly depends on the used operators. Using the uninorm operators in these processes the FLC components can be adapted to achieve better results. The program language environment, applied by simulation, supports the choosing of suitable fuzzy operators and their parameters. The simulation results are analyzed, depending on the efficiency of the operator choice in approximate reasoning model. © 2011 Scientific Assoc Infocomm.

Open Access: Yes

DOI: DOI not available

Intelligent robot cooperation with fuzzy communication

R. C. Pozna Á Ballagi L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2014-02-03

Volume: 530

Issue: Unknown

Page Range: 185-197

Description:

Designing the decision-making engine of a robot which works in a collaborative team is a challenging task. This is not only due to the complexity of the environment uncertainty, dynamism and imprecision, but also because of the coordination of the team has to be included in this design. The robots must be aware of other robots' actions in order to cooperate and to successfully achieve their common goal. In addition, decisions must be made in real-time and using limited computational resources. In this chapter we propose some novel algorithms for action selection in ambiguous tasks where the communication opportunities among the robots are very limited. © Springer International Publishing Switzerland 2014.

Open Access: Yes

DOI: 10.1007/978-3-319-03206-1_14

Optimization of the time-dependent traveling salesman problem using interval-valued intuitionistic fuzzy sets

P. Földesi Boldizsar Tuu-Szabo Ruba Almahasneh L. T. Koczy

Publication Name: Axioms

Publication Date: 2020-06-01

Volume: 9

Issue: 2

Page Range: Unknown

Description:

This study proposes a new model and approach for solving a realistic extension of the Time-Dependent Traveling Salesman Problem, by using the concept of distance between interval-valued intuitionistic fuzzy sets. For this purpose, we developed an interval-valued fuzzy degree repository based on the relations between rush hour periods and traffic regions in the "city center areas", and then we utilized the interval-valued intuitionistic fuzzy weighted arithmetic average to aggregate fuzzy information to be able to quantify the delay in any given trip between two nodes (cities). The proposed method is illustrated by a simple numerical example.

Open Access: Yes

DOI: 10.3390/AXIOMS9020053

Preface

Eloísa Ramírez-Poussa L. T. Koczy Jesús Medina-Moreno Alexander Šostak

Publication Name: Studies in Computational Intelligence

Publication Date: 2020-01-01

Volume: 819

Issue: Unknown

Page Range: v-ix

Description:

No description provided

Open Access: Yes

DOI: DOI not available

Fuzzy Signature Based Model in Material Handling Management

Ferenc Lilik B. Ferenczi L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2023-01-01

Volume: 1040

Issue: Unknown

Page Range: 169-179

Description:

Scheduling and management of material handling in functional production system are among the biggest challenges of logistics. Among several methods, linear programming gives exact solution to these kinds of problems, however, linear programming is rigid and requires specially trained personnel to operate. Fuzzy logic based systems—besides they work similarly to human thinking—seems to be easily implementable in such problems. In this paper we present a fuzzy signature based approach constructed on expert knowledge. Its results are compared to the results of linear programming in the same situations.

Open Access: Yes

DOI: 10.1007/978-3-031-07707-4_21

Preface

Rafal Wisniewski Janusz Kacprzyk Piotr Kulczycki Radko Mesiar L. T. Koczy

Publication Name: Advances in Intelligent Systems and Computing

Publication Date: 2020-01-01

Volume: 945

Issue: Unknown

Page Range: v-vii

Description:

No description provided

Open Access: Yes

DOI: DOI not available

Identification and dynamic analysis of crime hot-spots in Hungary by a complex Computer Intelligence approach

P. Földesi Boldizsar Tuu-Szabo Gábor Kovács Gergő Fogarasi L. T. Koczy Szilvia Nagy

Publication Name: Ines 2019 IEEE 23rd International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2019-04-01

Volume: Unknown

Issue: Unknown

Page Range: 247-252

Description:

In the field of forensic science, crime maps are widely used. The representation of the data and analysis could offer some steps forward for crime prevention. Clustering is able to help identify criminal hot-spots and further analysis designate which require intervention. The aim of this study is to present a first step in the analysis of Hungary-related criminal information.

Open Access: Yes

DOI: 10.1109/INES46365.2019.9109437

A population based metaheuristic for the minimum latency problem

P. Földesi Boldizsar Tuu-Szabo L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2019-01-01

Volume: 796

Issue: Unknown

Page Range: 113-121

Description:

In this paper we present a population based metaheuristic for solving the Minimum Latency Problem, which is the combination of bacterial evolutionary algorithm with local search techniques. The algorithm was tested on TSPLIB benchmark instances, and the results are competitive in terms of accuracy and runtimes with the state-of-the art methods. Except for two instances our algorithm found the best-known solution, and for the biggest tested instance it outperformed the best-known solution. The runtime was on average 30% faster than the most efficient method in the literature.

Open Access: Yes

DOI: 10.1007/978-3-030-00485-9_13

Preface

María Eugenia Cornejo Eloísa Ramírez-Poussa L. T. Koczy Jesús Medina-Moreno

Publication Name: Studies in Computational Intelligence

Publication Date: 2019-01-01

Volume: 794

Issue: Unknown

Page Range: v-vii

Description:

No description provided

Open Access: Yes

DOI: DOI not available

Grooming-enhanced multicast in multilayer networks with bacterial evolutionary algorithm

J. Botzheim Péter Soproni Tibor Cinkler L. T. Koczy

Publication Name: 8th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics Cinti 2007

Publication Date: 2007-12-01

Volume: Unknown

Issue: Unknown

Page Range: 211-225

Description:

In this paper we introduce new, bacterial evolutionary algorithm (BEA) based methods for routing unicast and multicast demands in grooming capable multi-layer optical wavelength division multiplexing (WDM) networks. The methods introduced are compared with both well known heuristic methods, accumulative shortest path heuristic (ASP) and minimum path heuristic (MPH), and as well as with ILP. We prove the strength of our approach by comprehensive simulations in our versatile simulator.

Open Access: Yes

DOI: DOI not available

Fuzzy signature and cognitive modelling for complex decision model

T. D. Gedeon L. T. Koczy Kok Wai Wong

Publication Name: Advances in Soft Computing

Publication Date: 2007-12-01

Volume: 42

Issue: Unknown

Page Range: 380-389

Description:

As data is getting more complex and complicated, it is increasingly difficult to construct an effective complex decision model. Two very obvious examples where such a need emerges are in the economic and the medical fields. This paper presents the fuzzy signature and cognitive modeling approach which could improve such decision models. Fuzzy signatures are introduced to handle complex structured data and problems with interdependent features. A fuzzy signature can also be used in cases where data is missing. The proposed fuzzy signature structure will be used in problems that fall into this category. This paper also investigates a novel cognitive model to extend the usage of fuzzy signatures. This Fuzzy Cognitive Signature Modelling will enhance the usability of fuzzy theory in modelling complex systems as well as facilitating complex decision making process based on ill structured information or data. © 2007 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-540-72434-6_38

Guest editorial: Uncertainty modelling and intelligent information processing

L. T. Koczy Kok Wai Wong

Publication Name: Memetic Computing

Publication Date: 2010-12-01

Volume: 2

Issue: 4

Page Range: 247-248

Description:

No description provided

Open Access: Yes

DOI: 10.1007/s12293-010-0052-5

On the Convergence of Input-Output Fuzzy Cognitive Maps

István Harmati L. T. Koczy

Publication Name: Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

Publication Date: 2020-01-01

Volume: 12179 LNAI

Issue: Unknown

Page Range: 449-461

Description:

Fuzzy cognitive maps are recurrent neural networks, where the neurons have a well-defined meaning. In certain models, some neurons receive outer input, while other neurons produce the output of the system. According to this observation, some neurons are categorized as input neurons and the others are the state neurons and output neurons. The output of the system is provided as a limit of an iteration process, which may converge to an equilibrium point, but limit cycles or chaotic behaviour may also show up. In this paper, we examine the existence and uniqueness of fixed points for two types of input-output fuzzy cognitive maps. Moreover, we use network-based measures like in-degree, out-degree and connectivity, to express conditions for the convergence of the iteration process.

Open Access: Yes

DOI: 10.1007/978-3-030-52705-1_33

Hierarchical fuzzy decision support methodology for dangerous goods packaging design

Péter Böröcz Kata Vöröskoi Gergő Fogarasi L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2020-01-01

Volume: 819

Issue: Unknown

Page Range: 1-7

Description:

In the field of logistics packaging (industrial-, or even customer packaging), companies have to take decisions on determining the optimal packaging solutions and expenses. The decisions often involve a choice between one-way (disposable) and reusable (returnable) packaging solutions. Even nowadays, in most cases the decisions are made based on traditions and mainly consider the material and investment costs, but many other aspects are important as well. Traditional (two-valued) logic is not suitable for modeling this problem, so the application of a fuzzy signature approach was considered. In a previous paper a fuzzy signature modeling the packaging decision was suggested, based on logistics expert opinions, in order to support the decision making process of choosing the right packaging system. The aim of this study is to improve the model and apply it for dangerous goods packaging.

Open Access: Yes

DOI: 10.1007/978-3-030-16024-1_1

A survey of the applications of fuzzy methods in recommender systems

P. Földesi Alex Tormási Brigita Sziová L. T. Koczy

Publication Name: Studies in Fuzziness and Soft Computing

Publication Date: 2018-01-01

Volume: 361

Issue: Unknown

Page Range: 483-495

Description:

In the past half century of fuzzy systems they were used to solve a wide range of complex problems, and the field of recommendation is no exception. The mathematical properties and the ability to efficiently process uncertain data enable fuzzy systems to face the common challenges in recommender systems. The main contribution of this paper is to give a comprehensive literature overview of various fuzzy based approaches to the solving of common problems and tasks in recommendation systems. As a conclusion possible new areas of research are discussed.

Open Access: Yes

DOI: 10.1007/978-3-319-75408-6_37

Some Dynamical Properties of Higher-Order Fuzzy Cognitive Maps

István Harmati L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2022-01-01

Volume: 959

Issue: Unknown

Page Range: 149-156

Description:

Fuzzy cognitive maps are recurrent neural networks, applied for modelling and simulation of complex dynamic systems. They have been successfully applied to many engineering problems. The conclusion about the system depends on the mathematical behaviour of an iteration, namely, a first-order recursion. The first-order dynamics have some limitations since it takes into account only the previous time step. To overcome these limitations higher-order memory-based fuzzy cognitive maps have been introduced, which use a sequence of preceding states to determine the next one. In this paper, some dynamical properties of higher-order fuzzy cognitive maps are analyzed. Particularly, the existence and uniqueness of equilibrium points and the stability are discussed.

Open Access: Yes

DOI: 10.1007/978-3-030-74970-5_17

Component based hardware-software system for fuzzy controlling of automated vehicles

A. Geresdi L. Siroki T. Pápai L. T. Koczy

Publication Name: Proceedings of Sefi and Igip Joint Annual Conference 2007 Joining Forces in Engineering Educations Towards Excellence

Publication Date: 2007-01-01

Volume: Unknown

Issue: Unknown

Page Range: 397-398

Description:

No description provided

Open Access: Yes

DOI: DOI not available

Novel Methods of FCM Model Reduction

F. Hatwágner L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2022-01-01

Volume: 955

Issue: Unknown

Page Range: 101-112

Description:

Fuzzy Cognitive Maps are widely applied to support decision making tasks. It is often hard for experts to create the model of a system that provides the required accuracy but simple enough to easily use in practice. In general, it is better to create complex models first, because they can be computationally reduced later until they preserve the required accuracy but become simple enough. Two novel Fuzzy Cognitive Map reduction methods based on K-Means and Fuzzy C-Means clustering are suggested in order to generate simplified models that hopefully mimic the behavior of the original model better than the already existing methods. After the quick overview of the existing techniques found in literature, a simple and a complex model of a real-life problem are reduced to varying degrees with the suggested new methods and with an existing one. The first results of the comparison are published in this paper, too.

Open Access: Yes

DOI: 10.1007/978-3-030-88817-6_12

Sparse fuzzy systems generation and fuzzy rule interpolation: A practical approach

Sz Kovacs T. D. Gedeon L. T. Koczy None Chong

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2003-07-11

Volume: 1

Issue: Unknown

Page Range: 494-499

Description:

In this paper, we explore the use of a sparse fuzzy system generation technique in conjunction with simple projection-based fuzzy rule interpolation, to generate sparse fuzzy systems with relatively few rules whilst still achieving reasonable system accuracy. Through setting a parameter value, the user is able to control, to some extent, the number of rules generated by the rule extraction technique. The rule interpolation approach enables the sparse fuzzy system to maintain a reasonable accuracy. The effectiveness of this approach is validated experimentally.

Open Access: Yes

DOI: DOI not available

The determination of the bitrate on twisted pairs by mamdani inference method

Ferenc Lilik L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2014-02-03

Volume: 530

Issue: Unknown

Page Range: 59-74

Description:

There are several methods for predicting the available maximal data transfer rate on dedicated telecommunication connections. This chapter presents some generally used techniques for prediction and some results of a Mamdani-type fuzzy reasoning system that is used in a telecommunication research aimed to create new predicting methods. At the end of the article the results of various methods are compared. All presented techniques are used for evaluation of the twisted-pair based local loops of the telecommunication access networks. © Springer International Publishing Switzerland 2014.

Open Access: Yes

DOI: 10.1007/978-3-319-03206-1_5

Modelling OCB and CWB by combined Fuzzy Signature model

D. Susniene Daiva Žostautiene Ojaras Purvinis L. T. Koczy

Publication Name: Economic Research Ekonomska Istrazivanja

Publication Date: 2021-01-01

Volume: 34

Issue: 1

Page Range: 1546-1565

Description:

Globalization and its challenges for organizations led to the understanding that employees can be a critical factor contributing to the organization’s performance. Therefore, various studies sought to understand employee’s behaviour that in itself encompasses various forms of engagement. One of the constructs defining engagement is citizenship behaviour (OCB) and counterproductive work behaviour (CWB). Based on previous researches, the study aims to contribute to the knowledge on the correlation between OCB and CWB considered as a behavioural engagement, from one side, and interplay of these constructs with the related constructs such as a trait engagement, perception of organization, state engagement, from another side. Since the empirical studies typically tend to concentrate on one or several factors separately, it is difficult to get a better understanding of relationship of all forms of engagement in corpore. To address this gap, we create a complex model of investigation developed to describe the linkage of the factors - OCB, CWB and related constructs under one umbrella and, by employing a combined statistical and Fuzzy Signature (FSig) model, we investigated the link with behavioural engagement. The present study covered one region of the northern part of Lithuania. It is based on 144 completed questionnaires from 35 companies. Findings support the assumption of the relationships of behavioural engagement (i.e. OCB and CWB) and the remaining multifaceted factors, and make a step forward by offering a new model for investigation the multifaceted phenomenon of employee engagement.

Open Access: Yes

DOI: 10.1080/1331677X.2020.1844581

Preface

Janusz Kacprzyk Piotr Kulczycki Radko Mesiar L. T. Koczy

Publication Name: Advances in Intelligent Systems and Computing

Publication Date: 2017-01-01

Volume: 462

Issue: Unknown

Page Range: v-vi

Description:

No description provided

Open Access: Yes

DOI: DOI not available

Extending the functional training approach for B-splines

Pedro M. Ferreira C. Cabrita A. E. Ruano L. T. Koczy

Publication Name: Proceedings of the International Joint Conference on Neural Networks

Publication Date: 2012-08-22

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

When used for function approximation purposes, neural networks belong to a class of models whose parameters can be separated into linear and nonlinear, according to their influence in the model output. This concept of parameter separability can also be applied when the training problem is formulated as the minimization of the integral of the (functional) squared error, over the input domain. Using this approach, the computation of the gradient involves terms that are dependent only on the model and the input domain, and terms which are the projection of the target function on the basis functions and on their derivatives with respect to the nonlinear parameters, over the input domain. This paper extends the application of this formulation to B-splines, describing how the Levenberg-Marquardt method can be applied using this methodology. Simulation examples show that the use of the functional approach obtains important savings in computational complexity and a better approximation over the whole input domain. © 2012 IEEE.

Open Access: Yes

DOI: 10.1109/IJCNN.2012.6252741

Learning the optimal parameter of the Hamacher t-norm applied for fuzzy-rule-based model extraction

László Gál Rita Lovassy L. T. Koczy I. J. Rudas

Publication Name: Neural Computing and Applications

Publication Date: 2014-01-01

Volume: 24

Issue: 1

Page Range: 133-142

Description:

Mamdani-type inference systems with trapezoidal-shaped fuzzy membership functions play a crucial role in a wide variety of engineering systems, including real-time control, transportation and logistics, network management, etc. The automatic identification or construction of such fuzzy systems input output data is one of the key problems in modeling. In the past years, the authors have investigated several different fuzzy t-norms, among others, algebraic and trigonometric ones, and the Hamacher product by substituting the standard "min" t-norm operation, in order to achieve better model fitting. In the present paper, the focus is on examining the general parametric Hamacher t-norm, where the free parameter quite essentially influences the quality of modeling and the learning capability of the model identification system. Based on a wide scope of simulation experiments, a quasi-optimal interval for the value of the Hamacher operator is proposed. © 2013 Springer-Verlag London.

Open Access: Yes

DOI: 10.1007/s00521-013-1499-3

Fuzzy Situational Maps: A new approach in mobile robot cooperation

R. C. Pozna Á Ballagi P. Földesi L. T. Koczy

Publication Name: Ines 2013 IEEE 17th International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2013-12-12

Volume: Unknown

Issue: Unknown

Page Range: 287-292

Description:

Intelligent robot cooperation tasks have very complex decision-making and computational processes. Collecting and calculating with a high amount of data is one of the weakest point of such system. In addition all of these it is necessary to process in real-time with limited computational capacity. In this paper we propose some novel algorithms for coping with these problems and give some information about the Fuzzy Situational Maps as a special case of the Fuzzy Signatures. An example takes to the field of warehouse logistics, managing and arranging boxes will be presented. © 2013 IEEE.

Open Access: Yes

DOI: 10.1109/INES.2013.6632828

On the Selection the Rule Membership Functions and Fuzzy Rule Interpolation

Ferenc Lilik Brigita Sziová Szonja Krisztina Szujo L. T. Koczy Szilvia Nagy

Publication Name: Studies in Computational Intelligence

Publication Date: 2022-01-01

Volume: 959

Issue: Unknown

Page Range: 111-118

Description:

In many real physical systems based fuzzy inference systems the rulebase is sparse thus interpolation or the change of the shape of the rules become necessary if the rulebase parameters are selected according to physical parameters of the systems. Often measurements contain noise and outlines which can draw the statistics of the measured data. In the present article based on two independent examples, namely telecommunication line evaluation and colonoscopy image processing, we study the effect of the selection of the rulebase parameters on the effectiveness of stabilized fuzzy KH interpolation.

Open Access: Yes

DOI: 10.1007/978-3-030-74970-5_13

A New Similarity Measure of Fuzzy Signatures with a Case Study Based on the Statistical Evaluation of Questionnaires Comparing the Influential Factors of Hungarian and Lithuanian Employee Engagement

D. Susniene Marta Szombathelyi Ojaras Purvinis L. T. Koczy

Publication Name: Mathematics

Publication Date: 2022-08-01

Volume: 10

Issue: 16

Page Range: Unknown

Description:

Similarity between two fuzzy values, sets, etc., may be defined in various ways. The authors here attempt introducing a general similarity measure based on the direct extension of the Boolean minimal form of equivalence operation. It is further extended to hierarchically structured multicomponent fuzzy signatures. Two versions of this measure, one based on the classic min–max operations and one based on the strictly monotonic algebraic norms, are proposed for practical application. A real example from management science is chosen, namely the comparison of employee attitudes in two different populations. This example has application possibilities in the evaluation and analysis of employee behaviour in companies as, due to the complex aspects in analysing multifaceted behavioural paradigms in organizational management, it is difficult for companies to make reliable decisions in creating processes for better social interactions between employees. In the paper, the authors go through the steps of building a model for exploring a set of different features, where a statistical pre-processing step enables the identification of the interdependency and thus the setup of the fuzzy signature structure suitable to describe the partially redundant answers given to a standard questionnaire and the comparison of them with help of the (pair of the) new similarity measures. As a side result in management science, by using an internationally applied standard questionnaire for exploring the factors of employee engagement and using a sample of data obtained from Hungarian and Lithuanian firms, it was found that responses in Hungary and Lithuania were partially different, and the employee attitude was thus in general different although in some questions an unambiguous similarity could be also discovered.

Open Access: Yes

DOI: 10.3390/math10162923

On a new doctoral (PhD) school in multidisciplinary engineering sciences

P. Földesi L. T. Koczy László Keviczky

Publication Name: 2011 International Conference on Information Technology Based Higher Education and Training Ithet 2011

Publication Date: 2011-10-04

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Széchenyi István University (SIU) is one of the youngest universities in Hungary, however, the school has three century old origins. The immediate predecessor of SIU was an engineering college founded 40 years ago. © 2011 IEEE.

Open Access: Yes

DOI: 10.1109/ITHET.2011.6018691

Preface

María Eugenia Cornejo István Harmati Eloísa Ramírez-Poussa Juan Moreno-García L. T. Koczy Jesús Medina-Moreno

Publication Name: Studies in Computational Intelligence

Publication Date: 2022-01-01

Volume: 955

Issue: Unknown

Page Range: v-viii

Description:

No description provided

Open Access: Yes

DOI: DOI not available

On classical and fuzzy Hough transform in colonoscopy image processing

Brigita Sziová Raneem Ismail L. T. Koczy Szilvia Nagy

Publication Name: IEEE AFRICON Conference

Publication Date: 2021-09-13

Volume: 2021-September

Issue: Unknown

Page Range: Unknown

Description:

Hough transform is used to find lines on edge-filtered images that are given in parametric form. As the fuzzy extension of the Hough transform has been proven to be more robust in environments where the lines to be found by them are not strictly following the formula given by the parametric equation of the Hough transform due to noise and weak and blurred contours, in the following considerations, we study the applicability of the circular fuzzy Hough transform for analyzing colonoscopy pictures and detecting colorectal polyps.

Open Access: Yes

DOI: 10.1109/AFRICON51333.2021.9570897

A robust fingerprint identification approach using a fuzzy system and novel rotation method

Ahmad A. Momani L. T. Koczy

Publication Name: Pattern Recognition

Publication Date: 2025-03-01

Volume: 159

Issue: Unknown

Page Range: Unknown

Description:

Forensic science has developed significantly in the last few decades. Its key role is to provide crime investigators with processed data obtained from the crime scene to achieve more accurate results presented in court. Biometrics has proved its robustness against various critical crimes encountered by forensics experts. Fingerprints are the most important biometric used until now due to their uniqueness and production low cost. The automated fingerprint identification system (AFIS) came into existence in the early 1960s through the cooperation of the countries: USA, UK, France, and Japan. Ever since it started to develop gradually because of the challenges found at the crime scenes such as fingerprints distortions and partial cuts which in turn can severely affect the final calculations made by experts. The vagueness of the results was the main motivation to build a robust fingerprint identification system that introduces new and enhanced methods in its stages to help experts make more accurate decisions. The proposed fingerprint identification system uses Fourier domain analysis for image enhancement, then the system cuts the image around the core point after applying the rotation and core point detection methods. After that, it calculates the similarity based on the distance between fingerprint histograms extracted using the Local Binary Pattern (LBP). The system's last step is to translate the results into a sensible form where it utilizes fuzziness to provide more possibilities for the answer. The proposed identification system showed high efficiency on FVC 2002 and FVC 2000 databases. For instance, the results of applying our system on FVC 2002 provided a set of three ordered matching candidates such that 97.5 % of the results provided the correct candidate as the first order, and the rest of 2.5 % provided the correct candidate as the second order.

Open Access: Yes

DOI: 10.1016/j.patcog.2024.111134

Using Fuzzy Cognitive Map approach to model the casual relationships in stakeholder management at companies

F. Hatwágner D. Susniene A. Buruzs A. Torma L. T. Koczy

Publication Name: 5th IEEE International Conference on Cognitive Infocommunications Coginfocom 2014 Proceedings

Publication Date: 2014-01-23

Volume: Unknown

Issue: Unknown

Page Range: 121-124

Description:

The aim of this paper is to investigate the operation of a Stakeholder Relationship Management System (SRMS) as a method for business management and project support by fuzzy approach. The criteria defined in connection with the SRMS will be modelled by using the Fuzzy Cognitive Map (FCM) approach in order to define the causality and weights of interconnections between the factors and to support decision making in that way.

Open Access: Yes

DOI: 10.1109/CogInfoCom.2014.7020431

Comparative study on credibility measures of type-2 and type-1 fuzzy variables and their application to a multi-objective profit transportation problem via goal programming

Dipak Kumar Jana Palash Sahoo L. T. Koczy

Publication Name: International Journal of Transportation Science and Technology

Publication Date: 2017-06-01

Volume: 6

Issue: 2

Page Range: 110-126

Description:

In real world applications supply, demand and transportation costs per unit of the quantities in multi-objective transportation problems may be hardly specified accurately because of the changing economic and environmental conditions. It is also significant that the time required for transportation should be minimized. In this paper, we have presented three reduction methods for a type-2 triangular fuzzy variable (T2TrFV) by adopting the critical value (CV). Three generalized expected values (optimistic, CV and pessimistic) are derived for T2TrFVs with some special cases. Then a multi-objective profit transportation problem (MOPTP) with fixed charge (FC) cost has been formulated and solved in type-2 fuzzy environment. Unit transportation costs, FC, selling prices, unit transport times, loading and unloading times, total supply capacities and demands are all considered as triangular Type-2 fuzzy numbers. The MOPTP has been converted into a single objective by using the goal programming technique and the weighted sum method. The deterministic model is then solved using the Generalized Reduced Gradient method Lingo 14.0. Numerical experiments with some sensitivity analysis are illustrated the application and effectiveness of the proposed approaches.

Open Access: Yes

DOI: 10.1016/j.ijtst.2017.06.002

Effect of the initial population construction on the DBMEA algorithm searching for the optimal solution of the traveling salesman problem

Boldizsar Tuu-Szabo Ali Jawad Ibada L. T. Koczy

Publication Name: Infocommunications Journal

Publication Date: 2022-09-01

Volume: 14

Issue: 3

Page Range: 72-78

Description:

There are many factors that affect the performance of the evolutionary and memetic algorithms. One of these factors is the proper selection of the initial population, as it represents a very important criterion contributing to the convergence speed. Selecting a conveniently preprocessed initial population definitely increases the convergence speed and thus accelerates the probability of steering the search towards better regions in the search space, hence, avoiding premature convergence towards a local optimum. In this paper, we propose a new method for generating the initial individual candidate solution called Circle Group Heuristic (CGH) for Discrete Bacterial Memetic Evolutionary Algorithm (DBMEA), which is built with aid of a simple Genetic Algorithm (GA). CGH has been tested for several benchmark reference data of the Travelling Salesman Problem (TSP). The practical results show that CGH gives better tours compared with other well-known heuristic tour construction methods.

Open Access: Yes

DOI: 10.36244/ICJ.2022.3.9

Preface

L. T. Koczy

Publication Name: Studies in Fuzziness and Soft Computing

Publication Date: 2024-01-01

Volume: 427

Issue: Unknown

Page Range: vii-xiii

Description:

No description provided

Open Access: Yes

DOI: DOI not available

Adaptive scheduling of optimization algorithms in the construction of interpolative fuzzy systems

Krisztián Balázs L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2013-11-22

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

This paper presents an adaptive scheduling approach applied for constructing interpolative fuzzy rule based systems. This is a continuation of our preceding work, where the same approach was used for dense fuzzy rule bases. © 2013 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZ-IEEE.2013.6622555

A concept reduction approach for fuzzy cognitive map models in decision making and management

F. Hatwágner A. Buruzs Elpiniki I. Papageorgiou L. T. Koczy

Publication Name: Neurocomputing

Publication Date: 2017-04-05

Volume: 232

Issue: Unknown

Page Range: 16-33

Description:

Policy making, strategic planning and management in general are complex decision making tasks, where the formulation of a quantitative mathematical model may be difficult or impossible due to lack of numerical data and dependence on imprecise verbal expressions. For such systems, knowledge representation graphs and cognitive maps are most familiar and often used for modelling complexity and aiding decision making. Fuzzy Cognitive Maps (FCM), as graph-based cognitive models, have been successfully used for knowledge representation and reasoning. In modelling complex systems usually a large number of concepts need to be considered. However, it is often difficult in real applications to find the appropriate number of concepts. Using only a few concepts is not enough to represent the modelled system with the required precision, and increasing the number of concepts increases the complexity of the model quadratically; it is burdensome to work with for the experts. The contribution of this paper is two-fold: (i) to propose a new concept reduction approach for FCM and (ii) to apply it on developing less complex FCM for management and decision making. The behaviour of reduced models is analysed through a number of scenarios with respect to the original complex system. The main idea of the reduction is a clustering based on fuzzy tolerance relations. The new approach is focused on reducing complexity in the modelling process, which provides a more transparent and easy to use model for policy makers. The applicability of the proposed method is demonstrated via literature examples and a solid waste management case study that initiated this research. The results clearly show the advantageous characteristics of the proposed concept reduction method for FCM and its aid in policy making.

Open Access: Yes

DOI: 10.1016/j.neucom.2016.11.060

Constructing dense fuzzy systems by adaptive scheduling of optimization algorithms

Krisztián Balázs L. T. Koczy

Publication Name: Proceedings of the 2013 Joint Ifsa World Congress and NAFIPS Annual Meeting Ifsa NAFIPS 2013

Publication Date: 2013-10-31

Volume: Unknown

Issue: Unknown

Page Range: 280-285

Description:

In this paper dense fuzzy rule based systems are constructed for solving machine learning problems. During the knowledge extraction process a scheduling approach is applied, which adaptively switches between the different optimization algorithms based on their convergence speed in the phases of the learning process, i.e. according to their respective local efficiency. © 2013 IEEE.

Open Access: Yes

DOI: 10.1109/IFSA-NAFIPS.2013.6608413

GENERAL PURPOSE CONDITION ASSESSMENT METHOD THAT CAN BE AUTOMATICALLY OPTIMISED FOR SPECIFIC OBJECTIVES

Ádám Bukovics Ferenc Lilik L. T. Koczy

Publication Name: Iet Conference Proceedings

Publication Date: 2024-01-01

Volume: 2024

Issue: 8

Page Range: 30-35

Description:

The maintenance and renovation of old (over 100 years old) residential buildings is one of the priority tasks in the last decades, because - especially in the inner areas of big cities - there are still a lot of them today, and therefore it has a decisive effect on the quality of life of many people. Since the structural design, materials, and condition of these types of residential buildings show many similarities, it is advisable to develop a uniform method for their condition assessment. A condition assessment and decision support model that is suitable for objective and uniform evaluation of this large number of old residential buildings and enables their energy-efficient maintenance and renovation as needed is being developed. The decision model consists of 4 main components (“Project info”, “Knowledge base”, “Preparatory work process”, “Fuzzy system”). For this method, a fuzzy signature-based decision model was developed, that can be used for the condition assessment of old residential buildings and for multi purpose intervention decision support. In this article, the main components are briefly overviewed and the automatic relationships between the individual elements of the project info and how it’s values affect the structure of the fuzzy signature is examined in details. Since the optimal structure of the fuzzy signature helps to make the right decision and the ideal use of the available resources, it is of great importance in terms of energy efficiency and sustainability. The other aim of automation is to make condition assessment even faster and more reliable.

Open Access: Yes

DOI: 10.1049/icp.2024.2677

Hierarchical Diagnostics and Risk Assessment for Energy Supply in Military Vehicles

P. Földesi Szabolcs Kocsis Szurke Dániel Csikor Ferenc Szauter L. T. Koczy

Publication Name: Energies

Publication Date: 2022-07-01

Volume: 15

Issue: 13

Page Range: Unknown

Description:

Hybrid vehicles are gaining increasing global prominence, especially in the military, where unexpected breakdowns or even power deficits are not only associated with greater expense but can also cost the lives of military personnel. In some cases, it is extremely important that all battery cells and modules deliver the specified amount of capacity. Therefore, it is recommended to introduce a new measurement line of rapid diagnostics before deployment, in addition to the usual procedures. Using the results of rapid testing, we recommend the introduction of a hierarchical three-step diagnostics and assessment procedure. In this procedure, the key factor is the building up of a hierarchical tree-structured fuzzy signature that expresses the partial interdependence or redundancy of the uncertain descriptors obtained from the rapid tests. The fuzzy signature structure has two main important components: the tree structure itself, and the aggregations assigned to the internal nodes. The fuzzy signatures that are thus determined synthesize the results from the regular maintenance data, as well as the effects of the previous operating conditions and the actual state of the battery under examination; a signature that is established this way can be evaluated by “executing the instructions” coded into the aggregations. Based on the single fuzzy membership degree calculated for the root of the signature, an overall decision can be made concerning the general condition of the batteries.

Open Access: Yes

DOI: 10.3390/en15134791

Fuzzy rule based systems as tools towards solving the "key problem of engineering"

L. T. Koczy

Publication Name: Studies in Fuzziness and Soft Computing

Publication Date: 2013-01-01

Volume: 298

Issue: Unknown

Page Range: 311-323

Description:

No description provided

Open Access: Yes

DOI: 10.1007/978-3-642-35641-4_46

Progressive bacterial algorithm

László Gál Rita Lovassy L. T. Koczy

Publication Name: Cinti 2012 13th IEEE International Symposium on Computational Intelligence and Informatics Proceedings

Publication Date: 2012-12-01

Volume: Unknown

Issue: Unknown

Page Range: 317-322

Description:

The purpose of this paper is to present a new version of the Bacterial Algorithms used for fuzzy rule base extraction called Progressive Bacterial Algorithm. In order to explore high quality models with very good speed of convergence towards the optimal rule base, we develop an improved version of the Bacterial Evolutionary and former Bacterial Memetic Algorithms. It is shown, in case of multidimensional reference problems, by comparing with existing methods, that an efficient and fast convergent tool is obtained. © 2012 IEEE.

Open Access: Yes

DOI: 10.1109/CINTI.2012.6496782

Adaptive improvement of a passive antilock brake control

Jimoh O. Pedro Samuel John L. T. Koczy

Publication Name: IEEE AFRICON Conference

Publication Date: 2011-12-12

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

The use of reliable or at least realistic friction models is a key factor in simulation studies related to antilock brake control systems. In the literature a plethora of strongly nonlinear tyre-road friction models are available. Certain models have singular expressions in the arguments of exponential terms in the vicinity of zero car body velocity though this region has practical significance. Since the parameters of these singular models may quickly vary in time with the variation of the road conditions their realtime identification was evaded in a paper that applied a simple observer instead. This method has been improved in the present paper by applying a novel adaptive technique for compensating the effects of the imprecisely known other (i.e. not related to the tyre-road friction) parameters. By the use of a particular friction model it was found via simulations that the adaptive technique can considerably shorten the braking distance. © 2011 IEEE.

Open Access: Yes

DOI: 10.1109/AFRCON.2011.6072040

Fuzzy neural networks stability in terms of the number of hidden layers

László Gál Rita Lovassy L. T. Koczy I. J. Rudas

Publication Name: 12th IEEE International Symposium on Computational Intelligence and Informatics Cinti 2011 Proceedings

Publication Date: 2011-12-01

Volume: Unknown

Issue: Unknown

Page Range: 323-328

Description:

This paper introduces an approach for studying the stability, and generalization capability of one and two hidden layer Fuzzy Flip-Flop based Neural Networks (FNNs) with various fuzzy operators. By employing fuzzy flip-flop neurons as sigmoid function generators, novel function approximators are established that also avoid overfitting in the case of test data containing noisy items in the form of outliers. It is shown, by comparing with existing standard tansig function based approaches that reducing the network complexity networks with comparable stability are obtained. Finally, examples are given to illustrate the effect of the hidden layer number of neural networks. © 2011 IEEE.

Open Access: Yes

DOI: 10.1109/CINTI.2011.6108523

Training electrical engineers on asynchronous logic circuits based on constant weight codes

Gábor Rózsa A. Nagy P. Keresztes L. T. Koczy

Publication Name: IEEE AFRICON Conference

Publication Date: 2011-12-12

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

The paper introduces a new way for teaching of delay insensitive asynchronous logic circuits. The studies start on high level models, which are VHDL implementations of Dennis-type static dataflow systems. Investigating the operation of the concurrent processes of these models, the main elements of the delay insensitive systems can be derived. Introducing constant weight 'm-of-n' codes immediately at the beginning of the course leads to a proper generalization. So the well known dual-rail code circuits can be considered as special cases of the constant weight code delay insensitive circuits. The paper presents briefly the design practice sessions for students. © 2011 IEEE.

Open Access: Yes

DOI: 10.1109/AFRCON.2011.6072041

Improved discrete bacterial memetic evolutionary algorithm for the traveling salesman problem

P. Földesi Boldizsar Tuu-Szabo L. T. Koczy

Publication Name: Advances in Intelligent Systems and Computing

Publication Date: 2017-01-01

Volume: 532

Issue: Unknown

Page Range: 27-38

Description:

In recent years a large number of evolutionary and other population based heuristics were proposed in the literature for solving NP-hard optimization problems. In 2015 we presented a Discrete Bacterial Memetic Evolutionary Algorithm (DBMEA) for The Traveling Salesman Problem. It provided results tested on series of TSP problems. In this paper we present an improved version of the DBMEA algorithm, where the local search is accelerated, which is the most time consuming part of the original DBMEA algorithm. This modification led to a significant improvement, the runtime of the improved DBMEA was 5– 20 times shorter than the original DBMEA algorithm. Our DBMEA algorithms calculate real value costs better than integer ones, so we modified the Concorde algorithm be comparable with our results. The improved DBMEA was tested on several TSPLIB benchmark problems and other VLSI benchmark problems and the following values were compared: - optima found by the improved DBMEA heuristic and by the modified Concorde algorithm with real cost values - runtimes of original DBMEA, improved DBMEA and modified Concorde algorithm. Based on the test results we suggest the use of the improved DBMEA heuristic for the more efficient solution of TSP problems.

Open Access: Yes

DOI: 10.1007/978-3-319-48517-1_3

A cooperation scenario for multiagent systems

R. C. Pozna Á Ballagi Nicuşor Minculete Radu Emil Precup L. T. Koczy

Publication Name: IEEE AFRICON Conference

Publication Date: 2011-12-12

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

This paper gives aspects related to a cooperation scenario in the framework of multiagent systems. The presentation is focused on a trivial multiagent system that consists of two agents, the Master and the Apprentice. The theoretical basis of the cooperation scenario is the definition of the most probable process, and two algorithms are used with this regard. The formulation of the cooperation scenario is exemplified for a case study that builds an architecture of successively placed bricks in the workspace. © 2011 IEEE.

Open Access: Yes

DOI: 10.1109/AFRCON.2011.6071961

Stability of fuzzy cognitive maps with interval weights

István Harmati L. T. Koczy

Publication Name: Proceedings of the 11th Conference of the European Society for Fuzzy Logic and Technology Eusflat 2019

Publication Date: 2020-01-01

Volume: Unknown

Issue: Unknown

Page Range: 756-763

Description:

In fuzzy cognitive maps (FCMs) based modelling paradigm, the complex system's behaviour is gathered by the causal connections acting between its main characteristics or subsystems. The system is represented by a weighted, directed digraph, where the nodes represent specific subsystems or features, while the weighted and directed edges express the direction and strength of causal relations between them. The state of the complex system represented by the so-called activation values of the nodes, that is computed by an iterative method. The FCM based decision-making relies on the assumption that this iteration reaches an equilibrium point (fixed point), but other types of behaviour, namely limit cycles and chaotic patterns may also show up. In practice, the weights of connections are estimated by human experts or machine learning methods. Both cases have their own uncertainty, which can be represented by using intervals as weights instead of crisp numbers. In this paper, sufficient conditions are provided for the existence and uniqueness of fixed points of fuzzy cognitive maps that are equipped with interval weights, which also ensure the global asymptotic stability of the system.

Open Access: Yes

DOI: DOI not available

A remark on adaptive scheduling of optimization algorithms

Krisztián Balázs L. T. Koczy

Publication Name: Communications in Computer and Information Science

Publication Date: 2010-12-01

Volume: 81 PART 2

Issue: Unknown

Page Range: 719-728

Description:

In this paper the scheduling problem of optimization algorithms is defined. This problem is about scheduling numerical optimization methods from a set of iterative 'oracle-based' techniques in order to obtain an as efficient as possible optimization process based on the given set of algorithms. Statements are formulated and proven about the scheduling problem and methods are proposed to solve this problem. The applicability of one of the proposed methods is demonstrated through a simple fuzzy rule based machine learning example. © Springer-Verlag Berlin Heidelberg 2010.

Open Access: Yes

DOI: 10.1007/978-3-642-14058-7_74

Hierarchical fuzzy system modeling by genetic and bacterial programming approaches

J. Botzheim Krisztián Balázs L. T. Koczy

Publication Name: 2010 IEEE World Congress on Computational Intelligence Wcci 2010

Publication Date: 2010-11-25

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

In this paper a method is proposed for constructing hierarchical fuzzy rule bases in order to model black box systems defined by input-output pairs, i.e. to solve supervised machine learning problems. The resultant hierarchical rule base is the knowledge base, which is constructed by using structure constructing evolutionary techniques, namely, Genetic and Bacterial Programming Algorithms. Applying hierarchical fuzzy rule bases is a way of reducing the complexity of the knowledge base, whereas evolutionary methods ensure a relatively efficient learning process. This is the reason of the investigation of this combination. © 2010 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2010.5584220

Decision making in multi-robot cooperation by fuzzy signature sets

Á Ballagi L. T. Koczy

Publication Name: 2010 IEEE World Congress on Computational Intelligence Wcci 2010

Publication Date: 2010-11-25

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

This paper presents some examples for fuzzy communication and intention guessing from the real life to the cooperation of intelligent mobile robots. In a special experimental environment a new communication approach is investigated for intelligent cooperation of autonomous mobile robots. Effective, fast and compact communication is one of the most important cornerstones of a high-end cooperating system. In this paper we propose a fuzzy communication system where the codebooks are built up by fuzzy signatures. We use cooperating autonomous mobile robots to solve some logistic problems. © 2010 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2010.5584821

An intelligent traffic congestion detection approach based on fuzzy inference system

F. Hatwágner Gergely Mikulai Mehran Amini L. T. Koczy

Publication Name: Saci 2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics Proceedings

Publication Date: 2021-05-19

Volume: Unknown

Issue: Unknown

Page Range: 97-104

Description:

Traffic congestion causes significant economic and social consequences. Instant detection of vehicular traffic breakdown has a pivotal role in intelligent transportation engineering. Common traffic estimators and predictors systems need traffic observations to be classified in their binary-set-nature computation methods which are unable to be an effective base for traffic modeling, since they are defined by precise and deterministic characteristics while traffic is known to be a highly complex and nonlinear system, which may be prescribed by uncertain models containing vague properties. This study aims at applying a new fuzzy inference model for predicting the level of congestion in such heterogeneous and convoluted networks, where the paucity of accurate and real-time data can cause problems in interpreting the whole system state by conventional quantitative techniques. The proposed fuzzy inference model is based on real data extracted from Hungarian network of freeways. As input variables traffic flow and approximate capacity of each segment are considered and level of congestion is regarded as output variable. In the model, a total number of 75 rules were developed on the basis of available datasets, percentile distribution, and experts' judgments. Designed model and analyzing steps are simulated and proven by Matlab fuzzy logic toolbox. The results illustrate correlations and relationships among input variables with predicting the level of congestion based on available resources. Furthermore, performed analyses beside their tractability in dealing with ambiguity and subjectivity are aligned with intelligent traffic modeling purposes in designing traffic breakdown-related alert or early warning systems, infrastructure and services planning, and sustainability development.

Open Access: Yes

DOI: 10.1109/SACI51354.2021.9465637

A highly accurate Mamdani fuzzy inference system for tennis match predictions

Boldizsar Tuu-Szabo L. T. Koczy

Publication Name: Fuzzy Optimization and Decision Making

Publication Date: 2025-03-01

Volume: 24

Issue: 1

Page Range: 99-127

Description:

This paper presents a Mamdani fuzzy inference system (FIS) designed for predicting tennis match outcomes with greater accuracy compared to existing models such as the Weighted Elo (WElo) ranking system. By integrating factors like historical performance, surface-specific proficiency, and recent form trends, the Mamdani FIS provides a nuanced approach to forecasting match results. Central to this method is the optimization of membership functions using a Bacterial Evolutionary Algorithm (BEA), which fine-tunes parameters to better model uncertainties inherent in sports analytics. This is the further development of Nawa and Furuhashi’s original approach of fuzzy system parameter discovery, which operates on the stricter conditions concerning the membership function shapes. The study demonstrates that the Mamdani FIS outperforms the traditional methods in both predictive accuracy and profitability of betting strategies. Through extensive validation, the model achieves higher accuracy and lower log loss metrics, indicating improved reliability in prediction outcomes. Additionally, the Mamdani FIS consistently yields higher returns on investment across various betting scenarios, showcasing its practical utility in sports betting applications. Overall, the proposed Mamdani FIS represents a robust tool for tennis match prediction, with potential extensions to other sports and predictive contexts. Future research may explore incorporating additional variables and applying this fuzzy inference approach to broader areas of sports analytics.

Open Access: Yes

DOI: 10.1007/s10700-025-09440-6

On the Applicability of Fuzzy Rule Interpolation and Wavelet Analysis in Colorectal Image Segment Classification

Ferenc Lilik Brigita Sziová Melinda Kovacs L. T. Koczy Szilvia Nagy

Publication Name: Studies in Fuzziness and Soft Computing

Publication Date: 2021-01-01

Volume: 394

Issue: Unknown

Page Range: 243-255

Description:

The automatic detection of colorectal polyps could serve as a visual aid for gastroenterologists when screening the population for colorectal cancer. A fuzzy inference based method was developed for determining whether a segment of an image has polyps. Its antecedent dimensions were the mean pixel intensity, the intensity’s standard deviation, the edge density, the structural entropies and the gradients, not only for the original image segments, but for its wavelet transformed versions. The method performed moderately well, even though the number of the input parameters was very large. In the present contribution we studied, that based on the necessary and usually applied conditions of the applicability of fuzzy rule interpolation, which antecedent dimensions should remain, and how omitting the other input parameters influences the results of the method.

Open Access: Yes

DOI: 10.1007/978-3-030-54341-9_21

Multilayer perceptrons constructed of fuzzy flip-flops

László Gál Rita Lovassy L. T. Koczy

Publication Name: Isciii 09 4th International Symposium on Computational Intelligence and Intelligent Informatics Proceedings

Publication Date: 2009-12-28

Volume: Unknown

Issue: Unknown

Page Range: 9-14

Description:

The target of this paper is to propose a hybrid combination of the three main branches of Computational Intelligence, namely Fuzzy Systems, Neural Networks and Evolutionary Computing. The function approximation properties of fuzzy J-K and D flip-flops based feedforward neural network optimized and trained with a novel evolutionary algorithm based technique; the Bacterial Memetic Algorithm with Modified Operator Execution Order (BMAM) is studied. © 2009 IEEE.

Open Access: Yes

DOI: 10.1109/ISCIII.2009.5342288

Quasi-Optimization of the Time Dependent Traveling Salesman Problem by Intuitionistic Fuzzy Model and Memetic Algorithm

P. Földesi Boldizsar Tuu-Szabo Ruba Almahasneh L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2020-01-01

Volume: 872

Issue: Unknown

Page Range: 239-253

Description:

The Traveling Salesman Problem (TSP) is an NP-hard graph search problem. Despite having numerous modifications of the original abstract problem, Time Dependent Traveling Salesman Problem (TD TSP) was one of the most realistic extensions under real traffic conditions. In TD TSP the edges between nodes are assigned higher costs (weights), if they were traveled during the rush hour periods, or crossed the traffic jam regions, such as the city center(s). In this paper we introduce an even more real-life motivated approach, the Intuitionistic Fuzzy Time Dependent Traveling Salesman Problem (IFTD TSP), which is a further extension of the TSP, and also of the classic TD TSP, with the additional notion of using intuitionistic fuzzy sets for the definition of uncertain costs, time, and space of the rush hour—traffic jam region affecting graph sections. In IFTD TSP we use fuzzy memberships and non-memberships sets for estimating the vague costs between nodes in order to quantify the behavior of traffic jam regions, and the rush hour periods. Since intuitionistic fuzzy sets are generalizations of classic fuzzy sets, our approach may be considered an extension and substitution of the original abstract TD TSP problem, even, of the (classic) Fuzzy TD TSP. Lastly, DBMEA (Discrete Bacterial Memetic Evolutionary Algorithm) was applied on the IFTD TSP model, the results of the simulation runs based on some extensions of the benchmarks generated from the original TD TSP data set showed quite good and promising preliminary results.

Open Access: Yes

DOI: 10.1007/978-3-030-34409-2_14

The application of fuzzy logic for the solving of conflicts in the dispositional tasks of a railway traffic control center

Tibor Héray Gábor Rózsa István Tömpe L. T. Koczy

Publication Name: IEEE AFRICON Conference

Publication Date: 2009-12-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

The paper considers a railway timetable related problem in a simplified form, generated by the delay of one or several incoming trains at a given station. Usually there are connecting trains in the timetable, especially in up to date periodic timetables and thus incoming delays might indicate the necessity of introducing a delay with connecting outgoing trains. A hierarchical fuzzy rule base is applied in order to determine the optimal outgoing delay, taking also usual restrictions into consideration. Three examples are shown. © 2009 IEEE.

Open Access: Yes

DOI: 10.1109/AFRCON.2009.5308167

Micro-Level Road Network Evaluation using Fuzzy Signature Rule Bases

Gergely Mikulai L. T. Koczy

Publication Name: Acta Polytechnica Hungarica

Publication Date: 2022-01-01

Volume: 19

Issue: 11

Page Range: 185-205

Description:

Nowadays, due to fast-increasing economic development, the current available road infrastructure is more and more crowded, which creates frustration for the people using them. In the current research, a model is proposed for authorities, companies and individuals, to choose the best available route(s) and road sections(s) for improvement measures, optimal delivery or commuting. In the proposed model, a fuzzy signature rule base, is introduced for commuters, which distinguishes all the relevant factors during commuting. The actual decision process is based on various input data, such as peoples’ habits, assumptions and preferences and various other factors.

Open Access: Yes

DOI: 10.12700/APH.19.11.2022.11.10

Modified bacterial memetic algorithm used for fuzzy rule base extraction

J. Botzheim László Gál L. T. Koczy

Publication Name: 5th International Conference on Soft Computing as Transdisciplinary Science and Technology Cstst 08 Proceedings

Publication Date: 2008-12-01

Volume: Unknown

Issue: Unknown

Page Range: 425-431

Description:

In this paper we discuss an improved version of the Bacterial Memetic Algorithm (BMA) used for fuzzy rule base extraction. In previous works we have found several ways to improve the original BMA. Some of them perform well rather in the case of more complex fuzzy rule base, and some of them perform well rather in the case of less complex fuzzy rule base. We have combined the improvements into a new version of the BMA that performs well in each case investigated. Copyright 2008 ACM.

Open Access: Yes

DOI: 10.1145/1456223.1456310

Improvements to the bacterial memetic algorithm used for fuzzy rule base extraction

J. Botzheim László Gál L. T. Koczy

Publication Name: Cimsa 2008 IEEE Conference on Computational Intelligence for Measurement Systems and Applications Proceedings

Publication Date: 2008-09-26

Volume: Unknown

Issue: Unknown

Page Range: 38-43

Description:

In this paper we discuss new methods to improve the Bacterial Memetic Algorithm (BMA) used for fuzzy rule base extraction. The first two methods are knot order violation handling methods which improves the performance of the BMA rather in the case of more complex fuzzy rule base. The third method is a new modification of the BMA in which the order of the operators is modified. This method improves the performance of the BMA rather in the case of less complex fuzzy rule base. ©2008 IEEE.

Open Access: Yes

DOI: 10.1109/CIMSA.2008.4595829

Context dependent reconstructive communication

T. D. Gedeon L. T. Koczy

Publication Name: Isciii 07 3rd International Symposium on Computational Intelligence and Intelligent Informatics Proceedings

Publication Date: 2007-09-25

Volume: Unknown

Issue: Unknown

Page Range: 13-19

Description:

No description provided

Open Access: Yes

DOI: 10.1109/ISCIII.2007.367354

Genetic and Bacterial Programming for B-Spline Neural Networks Design

J. Botzheim C. Cabrita A. E. Ruano L. T. Koczy

Publication Name: Journal of Advanced Computational Intelligence and Intelligent Informatics

Publication Date: 2007-03-01

Volume: 11

Issue: 2

Page Range: 220-231

Description:

The design phase of B-spline neural networks is a highly computationally complex task. Existent heuristics have been found to be highly dependent on the initial conditions employed. Increasing interest in biologically inspired learning algorithms for control techniques such as Artificial Neural Networks and Fuzzy Systems is in progress. In this paper, the Bacterial Programming approach is presented, which is based on the replication of the microbial evolution phenomenon. This technique produces an efficient topology search, obtaining additionally more consistent solutions.

Open Access: Yes

DOI: 10.20965/jaciii.2007.p0220

Topic identification by the combination of fuzzy thesaurus and complexity pursuit

L. T. Koczy S. Szaszkó

Publication Name: Advances in Information Systems Development New Methods and Practice for the Networked Society

Publication Date: 2007-01-01

Volume: 1

Issue: PART 1

Page Range: 329-340

Description:

No description provided

Open Access: Yes

DOI: 10.1007/978-0-387-70761-7_28

Efficient fuzzy cognitive modeling for unstructured information

T. D. Gedeon L. T. Koczy Kok Wai Wong

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2006-12-01

Volume: Unknown

Issue: Unknown

Page Range: 358-363

Description:

This paper presents an efficient fuzzy cognitive modeling which can handle granulation, organisation and causation. This cognitive modeling technique consists of multiple levels where the lowest level includes details required to make a decision or to transfer to the next stage. This Fuzzy Cognitive Modeling will enhance the usability of fuzzy theory in modeling complex systems as well as facilitating complex decision making process based on ill structured or missing information or data. © 2006 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2006.1681737

Two Stages Outlier Removal as Pre-Processing Digitizer Data on Fine Motor Skills (FMS) Classification Using Covariance Estimator and Isolation Forest

Surya Sumpeno Alex Tormási Nurul Zainal Fanani Festa Yumpi Rahmanawati K. Khamid Adri Gabriel Sooai Mauridhi Hery Purnomo L. T. Koczy

Publication Name: International Journal of Intelligent Engineering and Systems

Publication Date: 2021-08-01

Volume: 14

Issue: 4

Page Range: 571-582

Description:

The increase of the classification accuracy level has become an important problem in machine learning especially in diverse data-set that contain the outlier data. In the data stream or the data from sensor readings that produce large data, it allows a lot of noise to occur. It makes the performance of the machine learning model is disrupted or even decreased. Therefore, clean data from noise is needed to obtain good accuracy and to improve the performance of the machine learning model. This research proposes a two-stages for detecting and removing outlier data by using the covariance estimator and isolation forest methods as pre-processing in the classification process to determine fine motor skill (FMS). The dataset was generated from the process of recording data directly during cursive writing by using a digitizer. The data included the relative position of the stylus on the digitizer board. x position, y position, z position, and pressure values are then used as features in the classification process. In the process of observation and recording, the generated data was very huge so some of them produce the outlier data. From the experimental results that have been implemented, the level of accuracy in the FMS classification process increases between 0.5-1% by using the Random Forest classifier after the detection and outlier removal by using covariance estimator and isolation forest. The highest accuracy rate achieves 98.05% compared to the accuracy without outlier removal, which is only about 97.3%.

Open Access: Yes

DOI: 10.22266/ijies2021.0831.50

Fuzzy and Kohonen SOM based classification of different 0D nanostructures

Mark Farkas Ákos Nemcsics Antal Ürmös Zoltán Farkas Tamás Sándor L. T. Koczy

Publication Name: Sami 2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics Proceedings

Publication Date: 2017-03-16

Volume: Unknown

Issue: Unknown

Page Range: 365-370

Description:

In this paper, the clustering of the GaAs-based droplet epitaxially grown self-assembled nanostructures was investigated by soft-computing methods. The properties and the operation of these devices, depend on the type, the shape, the size, and their distribution of these 0 dimensional nanostructures. Because of this, it is very important to know, how and what kind of nanostructures can form, at the given technological parameters. Our goal is the classification of these nanostructures, in order to support the research and the production of these devices. Our solution is based on the shape factor calculation of the given nanostructure. In this work, two possible classification methods of nanostructures were introduced as well. First, the classification potential of the Kohonen Self-Organizing Mapping (SOM) was investigated. Second, the fuzzy inference system based classification was studied. In this case, the shape factor was determined by geometrical sizes of the nanostructures. In this paper the clustering was introduced, which supports many kinds of technology as well.

Open Access: Yes

DOI: 10.1109/SAMI.2017.7880335

Interpolative decisions in the fuzzy signature based image classification for liver CT

Ferenc Lilik Melinda Kovacs Szonja Krisztina Szujo L. T. Koczy Szilvia Nagy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2021-07-11

Volume: 2021-July

Issue: Unknown

Page Range: Unknown

Description:

In computer aided diagnostics image processing and classification plays an essential role. Image processing experts have been developing solutions for different types of problems, that can be related to image processing, however, due to the sensitivity of the data and the high cost of medical experts, these experimental methods usually have very limited use in real medical practice. The databases that are available are very limited, thus the elsewhere usual and extremely effective convolutional neural network or other automated learning methods are not so easy to adjust for medical image processing. To overcome this difficulty, this paper presents an expert knowledge based method which describes the decision structures by fuzzy signatures. Values of various properties of Computer Tomography images as e.g. density or homogeneity are being considered in these signatures that are different in all case of liver diseases. Because of the low number of samples available, fuzzy sets that describes the leafs of the signatures leads to sparse systems, hence interpolation is needed. However further investigations of other interpolation methods are planned, Stabilized Koczy-Hirota interpolation seems to be appropriate.

Open Access: Yes

DOI: 10.1109/FUZZ45933.2021.9494401

Control of traffic lights in high complexity intersections using hierarchical interpolative fuzzy methods

Csaba Gáspár József Hontvári Tibor Tari L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2006-12-01

Volume: Unknown

Issue: Unknown

Page Range: 1045-1048

Description:

This paper presents an approach for controlling very complex traffic intersections with hierarchical fuzzy rules. Fuzzy variables and rules are defined on a basic and also on a higher level. Simulation of road intersections with several lanes and road railroad intersection are presented. The results of a comparison of conventional cyclically controlled and fuzzy controlled systems will be shown © 2006 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2006.1681839

Decision support system for evaluating existing apartment buildings based on fuzzy signatures

G. Molnárka L. T. Koczy

Publication Name: International Journal of Computers Communications and Control

Publication Date: 2011-01-01

Volume: 6

Issue: 3

Page Range: 442-457

Description:

In historical district at European cities it is a major problem how to take decision on renovating or replacing existing buildings. This problem is imminent in Budapest (Hungary) in many traditional districts such as the Ferencváros district where we selected a compound area for further examination. By financial aid for the renovation of these buildings which awarded by Municipal Assembly of this district in question there is much uncertainty and confusion concerning how to decide whether or not and how to reconstruct a building where new private owners apply for support. In this paper we propose a formal evaluation method based on fuzzy signature rule bases (the formal being a special case of L-fuzzy object). Using the available expert knowledge we propose a fuzzy signature model including relevance weights and weighted aggregations for each node and parent node, respectively, so that as a result a single membership value may be calculated for each building in question. Linguistic labels for decision (such as worthless, average, highly valuable, etc.) are generated from the values thus obtained. Such linguistic calculations might be of help for the Municipal Assembly awarding financial support. A complete example wit 26 buildings is presented. © 2006-2011 by CCC Publications.

Open Access: Yes

DOI: 10.15837/ijccc.2011.3.2129

Estimating fuzzy membership functions parameters by the levenberg-marquardt algorithm

J. Botzheim C. Cabrita A. E. Ruano L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2004-12-01

Volume: 3

Issue: Unknown

Page Range: 1667-1672

Description:

In previous papers from the authors fuzzy model identification methods were discussed. The bacterial algorithm for extracting fuzzy rule base from a training set was presented. The Levenberg-Marquardt algorithm was also proposed for determining membership functions in fuzzy systems. In this paper the Levenberg-Marquardt technique is improved to optimise the membership functions in the fuzzy rules without Ruspini-partition. The class of membership functions investigated is the trapezoidal one as it is general enough and widely used. The method can be easily extended to arbitrary piecewise linear functions as well.

Open Access: Yes

DOI: 10.1109/FUZZY.2004.1375431

Construction site layout and building material distribution planning using hybrid algorithms

Krisztián Balázs Bence Kalmár András Kalmár L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2014-02-03

Volume: 530

Issue: Unknown

Page Range: 75-88

Description:

Chapters have been written previously about how genetic algorithms and other evolution-based algorithms could aid construction site layout planning. These articles presented approaches that solved of the layout problem by applying costs on the moving of construction materials across the site. Our goal was to build an algorithm which is specialized in solving problems of distributing building materials- brick for example-on a site by placing their pallets at the optimal spots, for every unit built from a given material to be within optimal reach. This article describes a solution of this problem for the engineering practice and interprets the slow but accurate method of the Hungarian Algorithm, further it proposes a Memetic Algorithm as a faster but almost as accurate solution. Conclusions are drawn about the usability of this method. © Springer International Publishing Switzerland 2014.

Open Access: Yes

DOI: 10.1007/978-3-319-03206-1_6

A new state reduction approach for fuzzy cognitive map with case studies for waste management systems

F. Hatwágner P. Földesi A. Buruzs L. T. Koczy

Publication Name: Advances in Intelligent Systems and Computing

Publication Date: 2015-01-01

Volume: 331

Issue: Unknown

Page Range: 119-127

Description:

The authors have investigated the sustainability of Integrated Waste Management Systems (IWMS). These systems were modeled by Fuzzy Cognitive Maps (FCM), which are known as adequate fuzzy-neural network type models for multi-component systems with a stable state. The FCM model was designed of thirty-three factors to describe the real world processes of IWMS in as much detailed and as much accurately as possible. Although, this detailed model meets the requirements of accuracy, the presentation and explanation of such a complex model is difficult due to its size.While there is a general consensus in the literature about a very much simplified model of IWMSs, detailed investigation lead to the assumption that a much more complex model with considerably more factors (components) would more adequately simulate the rather complex real life behavior of the IWMS.As the starting point we used the thirty-three component model based on the consensus of a workshop of experts coming from all areas of the IWMS (operation, regulation, management, etc.) and the set goal was to find the most accurate real model that could be obtained by analyzing and properly reducing this – very likely too much detailed, or atomized – model.In this paper, a new state reduction approach with three different metrics is presented. The practical aspects of the results gained by these methods are evaluated.

Open Access: Yes

DOI: 10.1007/978-3-319-13153-5_12

On the development of signatures for Artificial Intelligence applications

R. C. Pozna P. Földesi Radu Emil Precup L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2014-09-04

Volume: Unknown

Issue: Unknown

Page Range: 1304-1310

Description:

This paper illustrates developments of signatures for Artificial Intelligence (AI) applications. Since the signatures are data structures with efficient results in modeling of fuzzy inference systems and of uncertain expert systems, the paper starts with the analysis of the data structures used in AI applications from the knowledge representation and manipulation point of view. An overview on the signatures, on the operators on signatures and on classes of signatures is next given. Using the proto fuzzy inference system, these operators are applied in a new application of fuzzy inference system modeled by means of signatures and of classes of signatures.

Open Access: Yes

DOI: 10.1109/FUZZ-IEEE.2014.6891636

On wavelet based enhancing possibilities of fuzzy classification methods

Ferenc Lilik Brigita Sziová Levente Solecki L. T. Koczy Szilvia Nagy

Publication Name: Journal of Automation Mobile Robotics and Intelligent Systems

Publication Date: 2020-01-01

Volume: 14

Issue: 2

Page Range: 32-41

Description:

If the antecedents of a fuzzy classification method are derived from pictures or measured data, it might have too many dimensions to handle. A classification scheme based on such data has to apply a careful selection or processing of the measured results: either a sampling, re-sampling is necessary. or the usage of functions, transfor-mations that reduce the long, high dimensional observed data vector or matrix into a single point or to a low number of points. Wavelet analysis can be useful in such cases in two ways. As the number of resulting points of the wavelet analysis is approximately half at each filters, a consecutive application of wavelet transform can compress the me-asurement data, thus reducing the dimensionality of the signal, i.e., the antecedent. An SHDSL telecommunication line evaluation is used to demonstrate this type of appli-cability, wavelets help in this case to overcome the pro-blem of a one dimensional signal sampling. In the case of using statistical functions, like mean, variance, gradient, edge density, Shannon or Rényi entropies for the extraction of the information from a picture or a measured data set, and they don not produce enough information for performing the classification well enough, one or two consecutive steps of wavelet analysis and applying the same functions for the thus resulting data can extend the number of antecedents, and can dis-till such parameters that were invisible for these functions in the original data set. We give two examples, two fuzzy classification schemes to show the improvement caused by wavelet analysis: a measured surface of a combustion engine cylinder and a colonoscopy picture. In the case of the first example the wear degree is to be deter-mine, in the case of the second one, the roundish polyp content of the picture. In the first case the applied statistical functions are Rényi entropy differences, the structural entropies, in the second case mean, standard deviation, Canny filtered edge density, gradients and the entropies. In all the examples stabilized KH rule interpolation was used to treat sparse rulebases.

Open Access: Yes

DOI: 10.14313/JAMRIS/2-2020/18

On the sensitivity of type-2 fuzzy signatures and the generalizations of the extension principle

István Harmati L. T. Koczy

Publication Name: 2016 IEEE International Conference on Fuzzy Systems Fuzz IEEE 2016

Publication Date: 2016-11-07

Volume: Unknown

Issue: Unknown

Page Range: 1301-1307

Description:

When the exact mathematical model is not known or too difficult to handle, fuzzy signatures are useful tools in modeling and analysis of complex systems. In these cases the input values naturally have uncertainties, due to lack of knowledge or human activities. These built-in uncertainties influence the final decision about the system. In this paper we deal with the issue when the input parameters are not crisp values, but nonnegative fuzzy numbers, so we discuss the sensitivity of type-2 fuzzy signatures which are equipped with the weighted general mean as aggregation operator. The uncertainty of the result depends on the applied extension of real function to fuzzy numbers, so we discuss the case of Zadeh's extension principle, t-norm based extension and joint possibility distribution based extension of real functions, too.

Open Access: Yes

DOI: 10.1109/FUZZ-IEEE.2016.7737839

Hierarchical fuzzy decision support methodology for packaging system design

P. Földesi A. Buruzs Kata Vöröskoi Gergő Fogarasi L. T. Koczy

Publication Name: Advances in Intelligent Systems and Computing

Publication Date: 2020-01-01

Volume: 945

Issue: Unknown

Page Range: 85-96

Description:

In the field of logistics packaging (industrial-, or even customer packaging), companies have to take decisions on determining the optimal packaging solutions and expenses. The decisions often involve a choice between one-way (disposable) and reusable (returnable) packaging solutions. Even nowadays, in most cases the decisions are made based on traditions and mainly consider the material and investment costs. Although cost is an important factor, it might not be sufficient for finding the optimal solution. Traditional (two-valued) logic is not suitable for modelling this problem, so here the application of a fuzzy approach, because of the metrical aspects, a fuzzy signature approach is considered. In this paper a fuzzy signature modelling the packaging decision is suggested, based on logistics expert opinions, in order to support the decision making process of choosing the right packaging system. Two real life examples are also given, one in the field of customer packaging and one in industrial packaging.

Open Access: Yes

DOI: 10.1007/978-3-030-18058-4_7

Applying intelligent methods in logistics control

Tamás Hartványi Lajos Tóth L. T. Koczy

Publication Name: Iccc 2005 IEEE 3rd International Conference on Computational Cybernetics Proceedings

Publication Date: 2005-12-01

Volume: 2005

Issue: Unknown

Page Range: 71-74

Description:

The purpose of this research and development project is to construct the foundations of a logistics IT center with a universal and intermodal character, i.e., covering all modes of transportation and corresponding central functions related to warehouses and container terminals. Through its modular structure it is applicable to arbitrary concrete site dependent needs. It also contains intelligent elements, which offer suboptimal solutions to certain classic mathematical optimization problems connected to logistics, acceptable from a practical point of view and tractable in the computer science sense. In order to realize and implement this system, several basic research tasks both in logistics and IT will be solved. A model for a logistics center will be constructed, suitable for present infrastructural situation in Central and Eastern Europe but compatible with European Union standards.

Open Access: Yes

DOI: 10.1109/ICCCYB.2005.1511551

Man-machine cooperation without explicit communication

R. C. Pozna Á Ballagi L. T. Koczy

Publication Name: 2010 World Automation Congress Wac 2010

Publication Date: 2010-12-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

This paper presents a novel method for control cooperation between human and robots without any explicit communication line. We have proposed a fuzzy communication philosophy and implementation technique, where the code books are built up by fuzzy signatures. Fuzzy signatures are used as complex state description method for intention guessing and action selection. Robots cooperation means also to define the commune task. In order to understand their cooperation the robots must have complete knowledge about all possible states of the work or to understand the context by extract useful information from observation. Present paper focus on the second possibility. We propose a strategy of information extraction and context understanding based on an original data structure, the fuzzy signature and on a priori knowledge, the robot codebook. The paper starts by presenting the concept of the fuzzy signature and exemplify the idea of cooperation by context understanding. © 2010 TSI Press.

Open Access: Yes

DOI: DOI not available

Improved behavioral analysis of fuzzy cognitive map models

F. Hatwágner Gyula Vastag L. T. Koczy Vesa A. Niskanen

Publication Name: Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

Publication Date: 2018-01-01

Volume: 10842 LNAI

Issue: Unknown

Page Range: 630-641

Description:

Fuzzy Cognitive Maps (FCMs) are widely applied for describing the major components of complex systems and their interconnections. The popularity of FCMs is mostly based on their simple system representation, easy model creation and usage, and its decision support capabilities. The preferable way of model construction is based on historical, measured data of the investigated system and a suitable learning technique. Such data are not always available, however. In these cases experts have to define the strength and direction of causal connections among the components of the system, and their decisions are unavoidably affected by more or less subjective elements. Unfortunately, even a small change in the estimated strength may lead to significantly different simulation outcome, which could pose significant decision risks. Therefore, the preliminary exploration of model ‘sensitivity’ to subtle weight modifications is very important to decision makers. This way their attention can be attracted to possible problems. This paper deals with the advanced version of a behavioral analysis. Based on the experiences of the authors, their method is further improved to generate more life-like, slightly modified model versions based on the original one suggested by experts. The details of the method is described, its application and the results are presented by an example of a banking application. The combination of Pareto-fronts and Bacterial Evolutionary Algorithm is a novelty of the approach.

Open Access: Yes

DOI: 10.1007/978-3-319-91262-2_55

Agent-Based Intelligent Fuzzy Traffic Signal Control System for Multiple Road Intersection Systems

Tamrat Delessa Chala L. T. Koczy

Publication Name: Mathematics

Publication Date: 2025-01-01

Volume: 13

Issue: 1

Page Range: Unknown

Description:

Traffic congestion at a single intersection can propagate and thus affect adjacent intersections as well, potentially resulting in prolonged gridlock across an entire urban area. Despite numerous research efforts aimed at developing intelligent traffic signal control systems, urban areas continue to experience traffic congestion. This paper presents a novel agent-based fuzzy traffic control system for multiple road intersections. The proposed system is designed to operate in a decentralized manner, with each intersection having its own agent (fuzzy controller) functioning concurrently. The intelligent fuzzy controller of the system can recognize emergency vehicles, assess the queue length and waiting time of vehicles, measure the distance of vehicles from intersections, and consider the cumulated waiting times of short vehicle queues. Two distinct types of agent-based intelligent fuzzy traffic control systems were implemented for comparison: one involving collaboration between an agent and its immediate neighboring agent(s) (where one intersection exchanges traffic data with its immediate neighboring intersection(s)), and the other implementing a non-collaborative agent-based intelligent fuzzy traffic control system (where the individual intersection has no direct communication). Following the experimental simulations, the results were compared with those of existing intelligent fuzzy traffic control systems that lack any module to calculate the distance of the vehicles from the intersection. The results demonstrated that the proposed agent-based system of controllers exhibited superior performance compared with the existing fuzzy controllers in terms of indicators such as average waiting time, fuel consumption, and CO2 emissions. For instance, the proposed system reduced the average waiting time of vehicles at an intersection by 48.65% compared with the existing three-stage intelligent fuzzy traffic control system. In addition, a comparison was conducted between non-collaborating and collaborating agent-based intelligent fuzzy traffic control systems, where collaboration achieved better results than the non-collaborating system. In the simulation experiments, an interesting new feature emerged: despite any direct communication missing at multiple intersections, green waves evolved with time. This emergent feature suggests that fuzzy controllers have the potential to evolve and adapt to traffic complexity issues in urban environments when operating in an autonomous agent-based mode. This study demonstrates that agent-based fuzzy controllers can effectively communicate with one another to share traffic data and improve the overall system performance.

Open Access: Yes

DOI: 10.3390/math13010124

Quantum structure classification by Kohonen Self-Organizing Map and by Fuzzy C-Means algorithm

Mark Farkas Ákos Nemcsics Antal Ürmös L. T. Koczy

Publication Name: Icsse 2013 IEEE International Conference on System Science and Engineering Proceedings

Publication Date: 2013-11-18

Volume: Unknown

Issue: Unknown

Page Range: 313-318

Description:

Nowadays the nanostructures, formed on the way of self assembly are intensively investigated both in the basic and the applied sciences. In our paper, we investigate the structures on III-V compund semiconductor based materials, which are grown by epitaxial process. This process is analized by the beta version of Quantum Structure Analyzer 1.0, which is developed in C# langague, in the Microsoft© Visual Studio 2008 development environment. This software operates with the help of the Kohonen Self-Organizing Maps (SOM) algorithm and with the help of the Fuzzy C-Means algorithm. In present work, in the preface we give a short introduction of Molecular Beam Epitaxy (MBE), after this we introduce the algorithms, applied in this software. Finally, we demonstrate the results of the program. © 2013 IEEE.

Open Access: Yes

DOI: 10.1109/ICSSE.2013.6614682

Applicability of various wavelet families in fuzzy classification of access networks' telecommunication lines

Ferenc Lilik L. T. Koczy Szilvia Nagy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2017-08-23

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

The future of the smart society sets challenges for all types of existing telecommunication networks and links. For ensuring the optimal utilization of these networks precise performance predictions are necessary, especially in case of the symmetrical access networks with rather limited transmission capacity. It is also important to harness the already established infrastructure as long as it is technically possible, so that the use of the environmental resources would be minimal and the economical advantages would be maximal. In performance prediction of telecommunication links the high-dimensional input data, like the insertion loss spectrum, should be compessed. After reducing the dimension of the antecedent set, a fuzzy inference can be carried out for each of the lines. As the number of lines used for building the fuzzy sets is finite and the supports of the fuzzy set do not cover the whole space, a stabilized KH interpolation is used in the decision process. Wavelets constitute the basis of methods for compressing and analyzing data in many fields of science and technology. For the reduction of the input dimension, wavelets proved to be an effective tool. The applicability of various wavelet families with different sizes of filter coefficient sets are tested in the following considerations, with the result, that the wavelet type does not play an essential role as well as the length of the wavelets. Only the deepness of the wavelet transform influences essentially the goodness of the prediction: the remaining number of points should be 4 after the transformation.

Open Access: Yes

DOI: 10.1109/FUZZ-IEEE.2017.8015644

Interpolation in homogenous fuzzy signature rule bases

L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2017-08-23

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Fuzzy signature sets (FSigSets) are extensions of the original fuzzy set concept, and also of the Vector Valued Fuzzy Set notion. In a FSigSet rule base the (input) universe of discourse X is mapped into a set of hierarchically grouped fuzzy sets, and each element of X has a 'membership degree' consisting of a rooted tree with membership degrees at each leaf and aggregations at the intermediate vertices. The structure of the tree is identical for each element in the case of homogenous FSigSets, and so are the aggregations, depending only on the position of the vertex. Interpolation in fuzzy rule bases allows the calculation of a conclusion in the output universe Y belonging to an observation even if there are gaps in the rule base and the observation does not intersect with any of the antecedent sets. The key question here is how to determine the degree of similarity, or inversely, the distance, of any observation from the surrounding antecedents of the rules in the base, so that the distance incorporates the information involved with the close connection of the features in the sub-groups, and the aggregations expressing the form of this connection. A solution is proposed, and a pair of numerical examples is presented.

Open Access: Yes

DOI: 10.1109/FUZZ-IEEE.2017.8015393

Fuzzy pseudo-thesaurus based clustering of a folkloristic corpus

T. D. Gedeon L. T. Koczy S. Szaszkó

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2005-09-01

Volume: Unknown

Issue: Unknown

Page Range: 126-131

Description:

Automatic thesaurus extraction is essential for modern information retrieval. We develop a method for fuzzy pseudo-thesaurus based on word pair co-occurrence in documents. In this study it is presented, that considering the Word Frequency Degree counted on the whole corpus makes the obtained pseudo-thesaurus usable. Such parameters were found with which most of the obtained pairs of words were validated to be related by human expert. Among the extracted pairs and groups of words the relationship is often looser than synonymy, but they identify the frequently repeated topics of the corpus. We suggest the use of groups of closely related words for the definition of different topics and based on this clustering of the documents were performed.¹ © 2005 IEEE.

Open Access: Yes

DOI: DOI not available

Stability of Fixed-Point Values in Reduced Fuzzy Cognitive Map Models

F. Hatwágner L. T. Koczy

Publication Name: Studies in Fuzziness and Soft Computing

Publication Date: 2021-01-01

Volume: 393

Issue: Unknown

Page Range: 359-372

Description:

The authors have already presented their method for reducing oversized FCM models, and also have analyzed the prediction error of the reduced models. These investigations assumed that models have a single fixed-point attractor. The novelty of this paper is that it deals with the stability behavior of the fixed-point attractor value of original-reduced model pairs and compares the number of fixed-point attractors found, the asymptotic values of the concepts, and also checks if any limit cycles or chaotic behavior occur. The method of comparison and also the first results made with two real-life and one synthetic model are presented and some conclusions are taken.

Open Access: Yes

DOI: 10.1007/978-3-030-47124-8_29

The discrete bacterial memetic evolutionary algorithm for solving the one-commodity pickup-and-delivery traveling salesman problem

P. Földesi Boldizsar Tuu-Szabo L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2020-01-01

Volume: 819

Issue: Unknown

Page Range: 15-22

Description:

In this paper we propose a population based memetic algorithm, the Discrete Bacterial Memetic Evolutionary Algorithm for solving the one-commodity Pickup-and-Delivery Traveling Salesman Problem. The algorithm was tested on benchmark instances up to 100 nodes, and the results were compared with the state-of-the art methods in the literature. For all instances the DBMEA found optimal or close-optimal solutions.

Open Access: Yes

DOI: 10.1007/978-3-030-16024-1_3

The Effects of Preprocessing on Colorectal Polyp Detecting by Fuzzy Algorithm

Brigita Sziová L. T. Koczy Szilvia Nagy

Publication Name: Studies in Fuzziness and Soft Computing

Publication Date: 2021-01-01

Volume: 393

Issue: Unknown

Page Range: 347-357

Description:

In the following study the effects of two image preprocessing methods, namely Gaussian filtering and Wiener filtering, is studied on the results of a fuzzy inference method previously developed by the authors, for determining whether a colonoscopy picture segment contains any colorectal polyp. As earlier results show that less blurry, less compressed and less noisy images tend to be better classifiable, the effects of noise suppression with a Gaussian filter, which makes the images also blurrier, was beneficial on noisy, compressed images, and rather maleficent in good quality pictures. The effects of the Wiener filter, which both decreases noise and enhances edges, did not really manifest in classification improvement.

Open Access: Yes

DOI: 10.1007/978-3-030-47124-8_28

Developing a macroscopic model based on fuzzy cognitive map for road traffic flow simulation

F. Hatwágner Gergely Mikulai Mehran Amini L. T. Koczy

Publication Name: Infocommunications Journal

Publication Date: 2021-01-01

Volume: 13

Issue: 3

Page Range: 14-23

Description:

Fuzzy cognitive maps (FCM) have been broadly employed to analyze complex and decidedly uncertain systems in modeling, forecasting, decision making, etc. Road traffic flow is also notoriously known as a highly uncertain nonlinear and complex system. Even though applications of FCM in risk analysis have been presented in various engineering fields, this research aims at modeling road traffic flow based on macroscopic characteristics through FCM. Therefore, a simulation of variables involved with road traffic flow carried out through FCM reasoning on historical data collected from the e-toll dataset of Hungarian networks of freeways. The proposed FCM model is developed based on 58 selected freeway segments as the “concepts” of the FCM; moreover, a new inference rule for employing in FCM reasoning process along with its algorithms have been presented. The results illustrate FCM representation and computation of the real segments with their main road traffic-related characteristics that have reached an equilibrium point. Furthermore, a simulation of the road traffic flow by performing the analysis of customized scenarios is presented, through which macroscopic modeling objectives such as predicting future road traffic flow state, route guidance in various scenarios, freeway geometric characteristics indication, and effectual mobility can be evaluated.

Open Access: Yes

DOI: 10.36244/ICJ.2021.3.2

Application of interpolation-based fuzzy logic reasoning in behaviour-based control structures

Sz Kovacs L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2004-12-01

Volume: 3

Issue: Unknown

Page Range: 1543-1548

Description:

Some difficulties emerging during the construction of fuzzy behaviour-based control structures are inherited from the type of the applied fuzzy reasoning. The fuzzy rule base requested for many classical reasoning methods needed to be complete. In case of fetching fuzzy rules directly from expert knowledge e.g. for the behaviour coordination module, the way of building a complete rule base is not always straightforward. One simple solution for overcoming the necessity of the complete rule base is the application of interpolation-based fuzzy reasoning methods, since interpolation-based fuzzy reasoning methods can serve usable (interpolated) conclusion even if none of the existing rules is hit by the observation. These methods can save the expert from dealing with derivable rules and help to concentrate on cardinal actions only. For demonstrating the applicability of the interpolation-based fuzzy reasoning methods in behaviour-based control structures a simple interpolation-based fuzzy reasoning method and its adaptation for behaviour-based control will be introduced briefly in this paper.

Open Access: Yes

DOI: 10.1109/FUZZY.2004.1375404

Classifying the Complexity of Competency in Elementary School based on Supervised Learners

Tri Arief Sardjono I. Ketut Eddy Purnama Umi Laili Yuhana Eko Mulyanto Yuniarno Mauridhi Hery Purnomo L. T. Koczy

Publication Name: 2018 International Conference on Computer Engineering Network and Intelligent Multimedia Cenim 2018 Proceeding

Publication Date: 2018-07-02

Volume: Unknown

Issue: Unknown

Page Range: 280-284

Description:

Complexity of competency (CoC) expresses the difficulty level of a competency. The CoC is one of the important parameters for determining the minimum passing level of competency in an assessment system. In Indonesia, the value of CoC is defined by experts based on conditions of subject, students and teachers in each school. The definition process is determined subjectively, where different experts may evaluate CoC in different ways. This is a problem of data classification that requires an automated tool that copes with the amount of data and produces uniform results. To apply an intelligent classifier is essential to solve the issue. This study aims to find the best method for classifying the complexity of competency in Elementary School. Four supervised learning techniques, namely, Naïve Bayes, Multilayer Perceptron, Sequential Minimal Optimization, and RIPPER, were implemented to analyze the dataset. Based on an experiment with 203 data, we found that the Multilayer Perceptron achieved the best performance in the sense of Mean Absolute Error, Root Mean Squared Error, and Receiver Operating Characteristic value. At the same time SMO is better than all other methods in precision, recall, and F-Measure.

Open Access: Yes

DOI: 10.1109/CENIM.2018.8710883

An efficient new memetic method for the traveling salesman problem with time windows

P. Földesi Boldizsar Tuu-Szabo L. T. Koczy

Publication Name: Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

Publication Date: 2017-01-01

Volume: 10607 LNAI

Issue: Unknown

Page Range: 426-436

Description:

In this paper we present a new memetic algorithm, which is called Discrete Bacterial Memetic Evolutionary Algorithm for solving the Traveling Salesman Problem with time windows (TSPTW). This method is the combination of bacterial evolutionary algorithm with 2-opt and 3-opt local searches. The algorithm was already tested on symmetric Traveling Salesman Problem (TSP) benchmark instances up to 5000 cities. It showed good properties in terms of tour lengths, runtimes and predictability of runtimes, so we decide to examine other variants of TSP with our algorithm. With some slight modifications our method was tested on TSP with time windows benchmark instances. Our test results were compared with the state-of-the art methods. In most cases our algorithm found the best-known solutions, and in terms of solution quality and runtime it is the second best method.

Open Access: Yes

DOI: 10.1007/978-3-319-69456-6_35

Complex Framework for Condition Assessment of Residential Buildings

Ádám Bukovics Ferenc Lilik Balazs Lukacs L. T. Koczy

Publication Name: Lecture Notes in Civil Engineering

Publication Date: 2024-01-01

Volume: 444

Issue: Unknown

Page Range: 97-108

Description:

In the big cities of Europe large-scale construction of apartment buildings took place at the end of the 19th and at the beginning of the 20th century. In the process, buildings were created based on unique plans, but very similar to each other, containing similar technological solutions and built from similar building materials. Over the past 100 years, some of the buildings have been continuously maintained, while the condition of other buildings has deteriorated significantly. The renovation of these buildings has now become necessary and in many cases, unavoidable. In the current economic and energy situation, it is important that maintenance or conversion is carried out in a sustainable manner to the necessary extent. The method and extent of the interventions can be provided in a uniform manner with help of a computer system. We have developed a condition assessment and decision support model and algorithm that can be used for this purpose. We call it Complex Building’s Decision Support System based on Fuzzy Signatures (CBDF system). We use fuzzy signature-based model to handle uncertainties, inaccuracies and possibly missing data that occur during the condition assessment. The presented decision model prepares the status assessment based on 4 main components (project info, knowledge base, preparatory work process, fuzzy system). After defining the objectives (e.g., general condition assessment, evaluation from the perspective of accident prevention, examination of the possibility of roof installation), the system requests the necessary data and generates the fuzzy signature required for the condition assessment of the given building. Based on the input data for the specific project and the knowledge base, the decision model searches for failures and anomalies in the building based on the preparatory work process, manages the existing uncertainties and inaccuracies, and determines the load bearing surplus of the examined load bearing structures. Using the existing information and conclusions, based on various fuzzy set-based descriptors and aggregation operators, the condition assessment is prepared, and then, if necessary, the intervention proposal as well. The final goal of the decision model is to put a tool in the hands of experts examining the condition of buildings, which can be used to prepare uniform and objective assessments (also suitable for ranking) and to reduce error in condition assessment.

Open Access: Yes

DOI: 10.1007/978-3-031-48461-2_9

Delay propagation in a real life railway network controlled by a fuzzy logic rule base

Tibor Héray Gábor Rózsa Mark Farkas L. T. Koczy

Publication Name: 10th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics Cinti 2009

Publication Date: 2009-12-01

Volume: Unknown

Issue: Unknown

Page Range: 423-433

Description:

This paper considers a real-life railway timetable related problem, where a set of interconnected railway junction points form a railway network, which is essentially a directed graph with corresponding vertex and edge capacities representing railway tracks and railway platforms.The dynamic behavior of this model is driven by a timetable. Unforeseen weather and other external effects may contribute to delays in the timetable, which alters the behavior of the whole system. In this scenario a hierarchical fuzzy system is proposed that can suggest a possible outgoing delay for each train by evaluating a set of fuzzy rule bases using two input data. The first proposal does not take into account the possible propagation of delay in the whole railway network. In this article a negative feedback is applied on the hierarchical fuzzy system.The fuzzy sets are optimized by an evolution based global search metaheuristics.

Open Access: Yes

DOI: DOI not available

Non-associative fuzzy flip-flop with dual set-reset feature

Rita Lovassy L. T. Koczy

Publication Name: Sisy 2006 4th Serbian Hungarian Joint Symposium on Intelligent Systems

Publication Date: 2006-01-01

Volume: Unknown

Issue: Unknown

Page Range: 289-299

Description:

J-K flip-flops are the most general elementary units in sequential digital circuits. By extending Boolean operations to their respective fuzzy counterparts various fuzzy flipflops (F3) can be defined. Because of the axiomatic properties of fuzzy operations are considerably weaker then the properties satisfied by Boolean lattices, the minterm and maxterm type definitions of the same F3 are as a rule not equivalent. In former work we found a unique exception where simulation investigations lead to identical results for all parameter combinations examined. The base of this unique F3 is a pair of non-associative fuzzy connectives. In this paper the exact proof is given for the identity of the two definitions, i.e., for the uniqueness of the definition of this special non-associative F³.

Open Access: Yes

DOI: DOI not available

Applying bacterial memetic algorithm for training feedforward and fuzzy flip-flop based neural networks

J. Botzheim László Gál A. E. Ruano L. T. Koczy

Publication Name: 2009 International Fuzzy Systems Association World Congress and 2009 European Society for Fuzzy Logic and Technology Conference Ifsa Eusflat 2009 Proceedings

Publication Date: 2009-12-01

Volume: Unknown

Issue: Unknown

Page Range: 1833-1838

Description:

In our previous work we proposed some extensions of the Levenberg-Marquardt algorithm; the Bacterial Memetic Algorithm and the Bacterial Memetic Algorithm with Modified Operator Execution Order for fuzzy rule base extraction from input-output data. Furthermore, we have investigated fuzzy flip-flop based feedforward neural networks. In this paper we introduce the adaptation of the Bacterial Memetic Algorithm with Modified Operator Execution Order for training feedforward and fuzzy flipflop based neural networks. We found that training these types of neural networks with the adaptation of the method we had used to train fuzzy rule bases had advantages over the conventional earlier methods.

Open Access: Yes

DOI: DOI not available

The Extension of the Triple Fuzzy Time Dependent Travelling Salesman Problem Model, with a Discrete Bacterial Memetic Optimization Algorithm

Boldizsar Tuu-Szabo Ruba Almahasneh L. T. Koczy

Publication Name: Acta Polytechnica Hungarica

Publication Date: 2025-01-01

Volume: 22

Issue: 5

Page Range: 71-91

Description:

The Traveling Salesman Problem (TSP) is one of the most often studied NP-hard graph search problems. There have been numerous publications in the literature that applied various approaches to find the optimum or semi optimum solution. Although the problem is computationally intractable, but the Time Dependent Traveling Salesman Problem (TD TSP) is one of the most realistic extensions of the original TSP problem. In the TD TSP, the costs of edges between nodes vary, namely, they are assigned higher costs if they crossed a predefined oblong shaped area (to represent the jam region in the city center). Realizing that the jam regions and the rush hours costs on a tour are uncertain and can never be accurately represented by concrete numbers, we introduced the novel 3FTD TSP (Triple Fuzzy Time Dependent Traveling Salesman Problem); a fully fuzzified model of the original TD TSP. The 3FTD TSP utilizes fuzzy values for determining the costs between any two nodes within the traffic jam regions and during the rush hours periods more precisely. In this paper, we extend the 3FTD TSP further and apply it on the biggest universal instances in the literature in pursuit of testing the generality and applicability of the 3FTD TSP on real-life scenarios. To support the claim of the model’s efficiency, we propose the application of the DBMEA (Discrete Bacterial Memetic Evolutionary Algorithm), as a meta-heuristic and the classic GA (Genetic Algorithm) enabling the reader to compare the accuracy and the speed of (quasi-) optimum solutions convergence.

Open Access: Yes

DOI: 10.12700/aph.22.5.2025.5.4

Evaluating Deep Learning Algorithms for Freeway Mainstream Traffic Control

Ahmet Mehmet Karadeniz Mehran Amini L. T. Koczy

Publication Name: Lecture Notes in Networks and Systems

Publication Date: 2025-01-01

Volume: 1258 LNNS

Issue: Unknown

Page Range: 289-299

Description:

Traffic congestion is a universal problem that significantly impacts urban mobility and economic productivity. Accurate traffic flow prediction is crucial for efficient traffic management and congestion mitigation. Traditional methods often struggle to capture the complex temporal dependencies in traffic data. This study explores the effectiveness of Temporal Convolutional Network (TCN) models compared to Long Short-Term Memory (LSTM) models for predicting traffic volumes on freeway networks. Previous research has largely focused on LSTM models, leaving a gap in understanding the potential advantages of TCN models in this context. We address this gap by conducting a comprehensive comparison of LSTM and TCN models, training them on a dataset representing approximate traffic flow, and evaluating their performance using metrics such as Mean Squared Error (MSE), Mean Absolute Error (MAE), and coefficient of determination (R2). Our findings indicate that the TCN model outperforms the LSTM model, achieving lower MSE and MAE values and a higher R2 score. These results suggest that TCN models can more accurately predict traffic volumes under conditions with the least captured traffic data, offering a promising tool for real-time approximate traffic management and congestion prevention with reasonable prediction performance.

Open Access: Yes

DOI: 10.1007/978-3-031-81799-1_26

Simulation of Causal Relations of Stakeholder Management System by Using Fuzzy Cognitive Map Approach - A Comparison of Hungarian and Lithuanian Attitudes

F. Hatwágner D. Susniene Daiva Žostautiene A. Torma L. T. Koczy

Publication Name: Procedia Computer Science

Publication Date: 2015-01-01

Volume: 65

Issue: Unknown

Page Range: 880-890

Description:

Stakeholder Relationship Management Systems (SRMS) describe the general behavior of stakeholder relations at organizations. Knowing the interactions between the drivers of the SRMS helps to improve the efficiency of the whole system. This paper investigates the applicability of Fuzzy Cognitive Maps (FCM) to simulate the system dynamics and the causal connections within it. Previous investigations showed that FCM is a proper tool to analyze these relations and with the help of that the business management process and decision making in projects can be supported. The aim of this paper is to present the results of current simulations made with the help of FCM at Lithuanian and Hungarian organizations and to explain the causes of the identified differences. Beside that the paper investigates the influences of the modification of the threshold function's parameter on the final factor states.

Open Access: Yes

DOI: 10.1016/j.procs.2015.09.047

Fuzzy Hough transformation in aiding computer tomography based liver diagnosis

Brigita Sziová Melinda Kovacs L. T. Koczy Szilvia Nagy

Publication Name: IEEE AFRICON Conference

Publication Date: 2019-09-01

Volume: 2019-September

Issue: Unknown

Page Range: Unknown

Description:

In the liver many types of roundish lesions can appear, as well as near the liver. Finding the contour of such objects can improve both the segmentation of the liver from its environment, and the segmentation of the lesions within the liver. However, classical Hough transform, which is one of the main methods for finding objects described by a predefined parameterized formula, usually fails to identify these object as they possess not perfectly round or elliptic contours. A fuzzification of the Hough transform is described and suggested for using in image preprocessing for liver diagnosis based on CT images in this paper. Fuzzifying the Hough transform improves the detection of roundish contours.

Open Access: Yes

DOI: 10.1109/AFRICON46755.2019.9133793

On the Convergence of Sigmoidal Fuzzy Grey Cognitive Maps

István Harmati L. T. Koczy

Publication Name: International Journal of Applied Mathematics and Computer Science

Publication Date: 2019-09-01

Volume: 29

Issue: 3

Page Range: 453-466

Description:

Fuzzy cognitive maps (FCMs) are recurrent neural networks applied for modelling complex systems using weighted causal relations. In FCM-based decision-making, the inference about the modelled system is provided by the behaviour of an iteration. Fuzzy grey cognitive maps (FGCMs) are extensions of fuzzy cognitive maps, applying uncertain weights between the concepts. This uncertainty is expressed by the so-called grey numbers. Similarly as in FCMs, the inference is determined by an iteration process which may converge to an equilibrium point, but limit cycles or chaotic behaviour may also turn up. In this paper, based on the grey connections between the concepts and the parameters of the sigmoid threshold function, we give sufficient conditions for the existence and uniqueness of fixed points of sigmoid FGCMs.

Open Access: Yes

DOI: 10.2478/amcs-2019-0033

Mathematics and computational intelligence synergies for emerging challenges

Eloísa Ramírez-Poussa Juan Moreno-García L. T. Koczy Jesús Medina-Moreno

Publication Name: International Journal of Computational Intelligence Systems

Publication Date: 2021-01-01

Volume: 14

Issue: 1

Page Range: 818-820

Description:

No description provided

Open Access: Yes

DOI: 10.2991/ijcis.d.210121.001

Preface

María Eugenia Cornejo István Harmati L. T. Koczy Jesús Medina-Moreno

Publication Name: Studies in Computational Intelligence

Publication Date: 2023-01-01

Volume: 1040

Issue: Unknown

Page Range: v-ix

Description:

No description provided

Open Access: Yes

DOI: DOI not available

Fuzzy approach for the decision on disposable or returnable packaging

P. Földesi Péter Böröcz Kata Vöröskoi L. T. Koczy

Publication Name: Sustainability Switzerland

Publication Date: 2020-09-01

Volume: 12

Issue: 18

Page Range: Unknown

Description:

In modern logistics, companies and packaging engineers have to make decisions to find the optimal sustainable product-packaging system with adequate protection. The decision most often involves a decision option between disposable (single-trip) and reusable (returnable) packaging solutions. In practice, in most cases, this decision is based on historical data and traditions and only considers the packaging material and investment expenses. Although cost is an important factor, it is not the only one needed to find the optimal solution. Several other alternative factors further complicate the situation. Traditional (two-valued) logic is not able to model this problem. This study presents a novel technique to help the decision-making process using the application of fuzzy approach. The authors used three different fuzzy signatures connected by fuzzy rules to model the packaging decisions, which were based on logistics expert opinions. Practical examples are presented concerning both customer packaging (primary packaging) and industrial transport packaging (secondary packaging) as well.

Open Access: Yes

DOI: 10.3390/SU12187304

Fuzzy set based models comparative study for the td tsp with rush hours and traffic regions

P. Földesi Boldizsar Tuu-Szabo Ruba Almahasneh L. T. Koczy

Publication Name: Communications in Computer and Information Science

Publication Date: 2020-01-01

Volume: 1238 CCIS

Issue: Unknown

Page Range: 699-714

Description:

This study compares three fuzzy based model approaches for solving a realistic extension of the Time Dependent Traveling Salesman Problem. First, the triple Fuzzy (3FTD TSP) model, where the uncertain costs between the nodes depend on time are expressed by fuzzy sets. Second, the intuitionistic fuzzy (IFTD TSP) approach, where including hesitation was suitable for quantifying the jam regions and the bimodal rush hour periods during the day. Third, the interval-valued intuitionistic fuzzy sets model, that calculates the interval-valued intuitionistic fuzzy weighted arithmetic average (IIFWAA) of the edges’ confirmability degrees and non-confirmability degrees, was contributing in minimizing the information loss in cost (delay) calculation between nodes.

Open Access: Yes

DOI: 10.1007/978-3-030-50143-3_55

An efficient evolutionary metaheuristic for the traveling repairman (Minimum latency) problem

P. Földesi Boldizsar Tuu-Szabo L. T. Koczy

Publication Name: International Journal of Computational Intelligence Systems

Publication Date: 2020-01-01

Volume: 13

Issue: 1

Page Range: 781-793

Description:

In this paper we revisit the memetic evolutionary family of metaheuristics, called Discrete Bacterial Memetic Evolutionary Algorithm (DBMEA), whose members combine Furuhashi’s Bacterial Evolutionary Algorithm and various discrete local search techniques. These algorithms have proven to be efficient approaches for the solution of NP-hard discrete optimization problems such as the Traveling Salesman Problem (TSP) with Time Windows. This paper presents our results in solving the Traveling Repairman Problem (also called Minimum Latency Problem) with a DBMEA variant. The results are compared with state-of-the-art heuristics found in the literature. The DBMEA in most cases turned out to be faster than all other methods, and for the bigger benchmark instances it was also found to have better solutions than the former best-known results. Based on these test results we claim to have found the best approach and thus we suggest the use of the DBMEA for the Traveling Repairman Problem, especially for large instances.

Open Access: Yes

DOI: 10.2991/ijcis.d.200529.001

On the aggregation functions used in fuzzy signatures based medical image analysis

Ferenc Lilik Melinda Kovacs L. T. Koczy Szilvia Nagy

Publication Name: IEEE 23rd International Symposium on Computational Intelligence and Informatics Cinti 2023 Proceedings

Publication Date: 2023-01-01

Volume: Unknown

Issue: Unknown

Page Range: 409-414

Description:

The paper proposes the use of fuzzy signatures for modeling and analysis of pre-processed medical images, as an example, CT images of the liver are analyzed. Fuzzy signatures are used for the case of distinguishing larger and smaller malignant lesions from each other and from other (benign) nodular diseases in liver computed tomography images. As computed tomography phases are sometimes missing, the treatment of missing data is also briefly addressed. As the size of the malignant lesion influences its manifestation on the images, separate sub-signatures are developed for large and small lesions with the size being a separate layer of the signature. From the medical experts' point of view besides the tree structure of the signature it is crutial to determine the aggregations themselves, which model the ways experts fuse and combine the available information. For the subtrees for small and large lesions in the sub-roots algebraic multiplication seems to be the best fitting t-norm, while in the subtree weighted means.

Open Access: Yes

DOI: 10.1109/CINTI59972.2023.10381986

Construction of fuzzy signature from data: An example of S ARS pre-clinical diagnosis system

T. D. Gedeon L. T. Koczy Kok Wai Wong

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2004-12-01

Volume: 3

Issue: Unknown

Page Range: 1649-1654

Description:

There are many areas where objects with very complex and sometimes interdependent features are to be classified; similarities and dissimilarities are to be evaluated. This makes a complex decision model difficult to construct effectively. Fuzzy signatures are introduced to handle complex structured data and interdependent feature problems. Fuzzy signatures can also used in cases where data is missing. This paper presents the concept of a fuzzy signature and how its flexibility can be used to quickly construct a medical pre-clinical diagnosis system. A Severe Acute Respiratory Syndrome (SARS) pre-clinical diagnosis system using fuzzy signatures is constructed as an example to show many advantages of the fuzzy signature. With the use of this fuzzy signature structure, complex decision models in the medical field should be able to be constructed more effectively.

Open Access: Yes

DOI: 10.1109/FUZZY.2004.1375428

A discrete bacterial memetic evolutionary algorithm for the traveling salesman problem

P. Földesi Boldizsar Tuu-Szabo L. T. Koczy

Publication Name: 2016 IEEE Congress on Evolutionary Computation CEC 2016

Publication Date: 2016-11-14

Volume: Unknown

Issue: Unknown

Page Range: 3261-3267

Description:

This paper presents a Discrete Bacterial Memetic Evolutionary Algorithm (DBMEA) for the Traveling Salesman Problem. This algorithm combines the very efficient bacterial evolutionary algorithm with 2-opt and 3-opt local searches. Our approach was tested on TSPLIB and other VLSI benchmark problems. In this paper our computational results (minimal tour lengths, run times) are compared with other efficient TSP solver algorithms (Lin-Kernighan, Concorde). We will show that in significant number of the published benchmark problems the optimal tour was not found by the Concorde algorithm and the Lin-Kernighan heuristic because this approaches use an approximation substituting distances of points by the closest integer values. We suggest the substitution of the benchmark result set by the real optima calculated by the new DBMEA algorithm and the use of DBMEA heuristic as more precise for the solution of TSP and other NP-hard optimization problems.

Open Access: Yes

DOI: 10.1109/CEC.2016.7744202

Fuzzy rulebase parameter determination for stabilized KH interpolation based detection of colorectal polyps on colonoscopy images

Ferenc Lilik Brigita Sziová Raneem Ismail L. T. Koczy Szilvia Nagy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2020-07-01

Volume: 2020-July

Issue: Unknown

Page Range: Unknown

Description:

In the case of computer aided diagnosis it is advantageous to apply such computational intelligence methods, that can be related to direct measured data by means easily understandable to medical experts. Fuzzy reasoning, if the rulebase is generated from plausible statistical parameters of the image to be analysed, is easy to understand thus can be easily accepted by the society.In the case of colorectal polyps, which might develop into colorectal cancer, thus the population-wide screening would be advisable, more methods are available, but none of them is accepted as standard and effective method. A method based on simple statistical parameters and entropies of image segments is presented, and the effect of determining the rulebase parameters on the efficiency of finding the polyp segment is studied for stabilized Koczy-Hirota rule interpolation.

Open Access: Yes

DOI: 10.1109/FUZZ48607.2020.9177839

Analyzing employee behavior related questionnaires by combined fuzzy signature model

D. Susniene Daiva Žostautiene Ojaras Purvinis L. T. Koczy

Publication Name: Fuzzy Sets and Systems

Publication Date: 2020-09-15

Volume: 395

Issue: Unknown

Page Range: 254-272

Description:

The evaluation of data obtained from responses given to questionnaires in humanities and social sciences, such as management, linguistics, etc. is a complex task with the necessity of dealing with the inherent subjectivity and vagueness in such data. In this paper, a method based on fuzzy signatures (FSigs), suitable for analyzing questionnaires with hierarchically connected (partially) vague responses is proposed, and its applicability will be demonstrated by a real life problem; the partial analysis of an ongoing research examining employee behavior in various companies. The linkage of the factors hidden in the data bases obtained from the answers to the questionnaires, containing various factors interconnected in a more or less tight way, are represented by a hierarchical FSig system, allowing further evaluation and the discovery of emerging connections and deeper patterns among the responses, thus extending the idea of the original FSig model towards a more general, fuzzy-fuzzy signature approach. The method proposed here is a combination of some statistical elements with the Fuzzy Signature model, and it also uses Kohonen-maps in order to discover deeper structural components in the data pool. As FSigs are suitable to express hierarchically structured connections among vague and imprecise features of the individual data, the statistical analysis helps reveal the degrees of redundancies and the closeness of connectedness of the individual elements within the responses, and thus enable the construction of a relevant FSig tree graph for the data on hand, while further expert domain knowledge helps with determining the proper fuzzy aggregations in the intermediate nodes of the FSigs. The case study presented is based on data obtained from North Lithuanian companies. The results of the case study focusing on the analysis of the connection between OCB and CWB, and other factors, disclose some interesting and, partly unexpected, results. They indicate a strong and unambiguous relationship between career satisfaction and OCB, which is not very surprising. However, it is found that there is no relationship with gender, age, and actual position in the company, which are generally supposed to be determining factors. These results may be further validated by expert knowledge, and thus the new combined method for evaluating structured multicomponent data and internal dependencies is adequate.

Open Access: Yes

DOI: 10.1016/j.fss.2020.04.018

A combined fuzzy and least squares method approach for the evaluation of management questionnaires

D. Susniene Ojaras Purvinis L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2020-01-01

Volume: 819

Issue: Unknown

Page Range: 157-165

Description:

A set of answers to questions to employees of various companies in Lithuania may refer to various positive and negative aspects of the attitudes of employees. These are called Organizational Citizenship Behavior (positive) and Counterproductive Work Behavior (negative). The components in the answers may be grouped by expert knowledge, and by statistical analysis and, according to these approaches, based on expert domain knowledge by management specialists, fuzzy signature structures describing the mutual effects of single elements in the questionnaire may be created. There are some slight differences between the two results, that indicate that expert knowledge is sometimes not objective. An additional step applying hybrid Generalised Reduced Gradient algorithm and Genetic Evolutionary Algorithm for heuristic optimization of the aggregation parameters in the Fuzzy Signatures reveals a final model according to the responses. These latter results raise some new questions, including the idea of the use of undeterministic graphs, thus resulting in Fuzzy Fuzzy Signatures. The method could be applied to other similar multicomponent vague data pools.

Open Access: Yes

DOI: 10.1007/978-3-030-16024-1_20

Statistical Analysis of the Performance of the State-of-the-Art Methods for Solving TSP Variants

P. Földesi Boldizsar Tuu-Szabo L. T. Koczy

Publication Name: Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

Publication Date: 2019-01-01

Volume: 11909 LNAI

Issue: Unknown

Page Range: 255-262

Description:

In this paper we analyze the efficiency of the state-of-the-art methods for solving two TSP variants, the Traveling Salesman Problem with Time Windows and one-commodity Pickup-and-Delivery Traveling Salesman Problem. Three models (polynomial, exponential, square-root exponential) were fitted to the mean run times of each method. The parameters of the curves, the R²-values and the RMSE values were compared.

Open Access: Yes

DOI: 10.1007/978-3-030-33709-4_23

Mobile Robot Environment Representation Through Fuzzy Signatures-Integrated Quadtrees

Csaba Hajdu Ahmet Mehmet Karadeniz L. T. Koczy

Publication Name: Romanian Journal of Information Science and Technology

Publication Date: 2025-01-01

Volume: 28

Issue: 1

Page Range: 103-116

Description:

This paper presents an innovative environment representation technique for mobile robots, incorporating obstacle detection within their operational space. Leveraging the fuzzy signature method, this approach uses quadtrees for efficient data organization. A set of fuzzy rules evaluates feature points to ascertain the relevance of identified obstacles. These points and their fuzzy associations are systematically arranged using a quadtree structure. The environmental model is reconstructed by traversing this tree and applying the established fuzzy rules. This paper has achieved a high-resolution grid representation of 0.1m within a 20m×20m area. Notably, the inference operation completes in just 0.5 ms, underscoring the method’s efficiency. Additionally, the technique is optimized for low memory consumption, demonstrating effective resource management even on older PCs, such as an Intel Core Duo 2 with 16 GB RAM. This representation is designed to support advanced robotic functions, such as obstacle navigation in a distributed computing environment.

Open Access: Yes

DOI: 10.59277/ROMJIST.2025.1.09

Fuzzy signature based model for qualification and ranking of residential buildings

Ádám Bukovics L. T. Koczy

Publication Name: International Journal for Housing Science and Its Applications

Publication Date: 2013-12-02

Volume: 37

Issue: 4

Page Range: 217-227

Description:

At the end of the 19th and at the beginning of the 20th centuries Budapest the capital of the Hungarian kingdom underwent a significant development. During this period the number of inhabitants of the city multiplied, as a consequence several new city districts were constructed. The functional and structural arrangement of these new residential buildings was very similar in respect of the materials used and the technologies applied. A considerable part of these buildings still constitutes the determining element of the townscape. It is one of the most burning issues of the present day Budapest that a part of these buildings are in very bad condition. Due to the limited financial resources it is an essential task to set up priority ranking of the renovation, upgrading and renewal of buildings with similar arrangement. In our case the traditional (two-valued) logic is unsuitable for modelling or handling the given phenomenon. When describing the status of a load-bearing building structure the terminology of "appropriate condition" cannot be handled by Boolean logic, since it cannot be strictly determined where the borderline is between appropriate or inappropriate condition. In the case of the majority of the linguistic characteristics of this type there is a well noticeable joint element, which expresses a kind of inaccuracy or uncertainty. For such tasks the application of fuzzy signatures is considered to be one of the possible solutions. The fuzzy type inaccuracy somehow links with human thinking. Fuzzy logic is an extension of the two-valued logic, which makes it possible to define transitions, too. By applying the fuzzy singleton signatures a status-determining and ranking model was created, which is suitable for the qualification and ranking of buildings of similar age and structural arrangement. This model was used for the first time on a database, which is based on expert opinions, relating to a given stock of residential building. The modelling of the load-bearing structural condition of the residential buildings is a complicated task, the components where of are well-structured and a hierarchical structure can be built therefrom. Based on the foregoing a tree-structure, necessary for the examination of the load-bearing structures of buildings, has been proposed. In this framework primary and secondary structures were distinguished during the examination, which would be linked with qualification values based on their arrangement, materials and conditions (in accordance with fuzzy logic). The significance of the load-bearing structure of various building elements was taken into account by using relevance weights. For the aggregation of the fuzzy singleton signature the Weighted Relevance Aggregation Operation (WRAO) was used. The aggregate status descriptors, characteristic of the status of a building, provided the basis for the ranking of buildings in case of a certain stock of buildings. Discrepancies of the results achieved by method using membership functions of approximate and fine set of values, conclusions were drawn as to when and which method should be used in practise. The results of this study may make it easier to realize rehabilitation ideas of similar residential areas, and also can be efficiently used during utilization and renewal of certain buildings in bad condition. Copyright © 2013 IAHS.

Open Access: Yes

DOI: DOI not available

Linear fuzzy rule base interpolation using fuzzy geometry

Suman Das L. T. Koczy Debjani Chakraborty

Publication Name: International Journal of Approximate Reasoning

Publication Date: 2019-09-01

Volume: 112

Issue: Unknown

Page Range: 105-118

Description:

Fuzzy Rule Interpolation (FRI) provides an interpretable decision in sparse fuzzy rule based system. The objective of this work is to establish a mathematical demonstration of the pattern of existing fuzzy rule base using fuzzy geometry. Though several authors contributed on fuzzy rule base interpolation but there is a need to generate closed mathematical form of interpolating pattern. The present work is an initiative to demonstrate the same. First part of this paper presents some spatial geometrical transformation of a fuzzy point. In the second part of this paper, a new FRI scheme is suggested using fuzzy geometry with above mentioned transformation. The proposed method operates in two different steps. In the first step, all the fuzzy rules are converted into fuzzy sets or mostly fuzzy points in higher dimension by using mathematical operator on the individual of antecedent and consequent parts. All rules or fuzzy points are then joined with a class of fuzzy line segments (FLS). Second step considers the identification of mathematical pattern of the interpolated piecewise linear fuzzy polynomial which is able to compute the desired conclusion of a given observation. The presented method not only associates the FRI technique to classical interpolation technique, but also promises to provide the geometrical visualization of the behaviour of fuzzy sets during the interpolation process.

Open Access: Yes

DOI: 10.1016/j.ijar.2019.05.004

Applicability of fuzzy flip-flops in the implementation of neural networks

László Gál Rita Lovassy L. T. Koczy

Publication Name: 9th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics Cinti 2008

Publication Date: 2008-12-01

Volume: Unknown

Issue: Unknown

Page Range: 333-344

Description:

The concept of various type fuzzy flip-flops (F³) has already been proposed. We have done some investigations on a large scope of F ³s based on different t-norms and conorms. Also we have shown that a few F³ types are suitable for realizing neurons in multilayer perceptrons. The aim of this paper is to present a comparison of the performance of several type neural networks based on fuzzy J-K and also fuzzy D flip-flops (the latter derived from the former type). The behavior of algebraic, Yager, Dombi and Hamacher type fuzzy flip-flop neural networks are presented. The best fitting t-norm and corresponding fuzzy flip-flop type will be presented in terms of function approximation capability.

Open Access: Yes

DOI: DOI not available

Modelling twofold uncertainty in the condition assessment of residential buildings using interval valued fuzzy signatures

Ádám Bukovics István Harmati L. T. Koczy

Publication Name: 2016 IEEE Symposium Series on Computational Intelligence Ssci 2016

Publication Date: 2017-02-09

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

In this study we will describe an intervention decision-support method related to residential buildings, which is modelling the condition of buildings based on linguistic expert opinions so that it is capable of taking into consideration the uncertainties included in the expert opinions. Fuzzy signature-based model is used, wherein the uncertainties are integrated into the system by applying interval valued fuzzy sets, as well as linguistic hedges. The result will be a fuzzy set for each building, describing the condition of the whole building, specify the bourdary values between which the condition of the building may fall.

Open Access: Yes

DOI: 10.1109/SSCI.2016.7849994

Improved fuzzy-based single-stroke character recognizer

Alex Tormási L. T. Koczy

Publication Name: Proceedings of the 2013 Joint Ifsa World Congress and NAFIPS Annual Meeting Ifsa NAFIPS 2013

Publication Date: 2013-10-31

Volume: Unknown

Issue: Unknown

Page Range: 430-435

Description:

In this paper we present two modified and improved versions of the formerly published Fuzzy-Based Single-Stroke Character Recognizer (FUBAR) algorithm. After introducing the original method, the study investigates the effects of two different improvements of the designed algorithm. The first extension is the use of symbol-dependent fuzzy grids to extract symbol features; the second one is the use of rule weights in hierarchical rule-bases. The accuracy and efficiency of the extended FUBAR algorithms are compared to previous results. © 2013 IEEE.

Open Access: Yes

DOI: 10.1109/IFSA-NAFIPS.2013.6608439

Parameter optimisation in fuzzy flip-flop-based neural networks

László Gál Rita Lovassy L. ászlóT Kóczy L. T. Koczy

Publication Name: International Journal of Reasoning Based Intelligent Systems

Publication Date: 2010-01-01

Volume: 2

Issue: 3-4

Page Range: 237-243

Description:

This paper presents a method for optimising the parameters of fuzzy flip-flop-based neural networks (FNN) consisting of fuzzy J-K and D flip-flop neurons based on various popular fuzzy operations using bacterial memetic algorithm with the modified operator execution order (BMAM). In early works, the authors proposed the Levenberg-Marquardt algorithm (LM) a widely used second order gradient type training algorithm for fuzzy neural networks variables optimisation. The BMAM local and global search evolutionary approach is a bacterial type memetic algorithm which executes several LM cycles during the bacterial mutation after each mutational step, using the LM method more efficiently. Numerical experiments were performed to show the function approximation capability of various quasi optimised FNN types based on fuzzy J-K and D flip-flop neurons using algebraic, Lukasiewicz, Yager, Dombi, Hamacher and Frank norms, trained with LM method and BMAM algorithm. © 2010 Inderscience Enterprises Ltd.

Open Access: Yes

DOI: 10.1504/IJRIS.2010.036869

Historical origin of the fine structure constant: Part II: Subtilis structurae constans inversae arboris dei

P. Várlaki L. T. Koczy I. J. Rudas

Publication Name: Acta Polytechnica Hungarica

Publication Date: 2011-09-22

Volume: 8

Issue: 2

Page Range: 161-196

Description:

In this paper we intend to show in some great medieval works that are indeed or very likely linked to St Stephen's court the central role of the number-archetype 137 organizing "fine structures", together with quaternary and denary proto-Kabbalistic "systems", as a possible primordial image and "model" of the quantum-physical fine structure. This is associated with the four quantum-numbers and the fine structure constant (FSC) concept, in the sense that Jung and Pauli discussed similar problems upon the scientific and spiritual history of the Western Thought.

Open Access: Yes

DOI: DOI not available

Different Chromosome-based Evolutionary Approaches for the Permutation Flow Shop Problem

Krisztián Balázs L. T. Koczy Zoltán Horváth

Publication Name: Acta Polytechnica Hungarica

Publication Date: 2012-05-28

Volume: 9

Issue: 2

Page Range: 115-138

Description:

This paper proposes approaches for adapting chromosome-based evolutionary methods to the Permutation Flow Shop Problem. Two types of individual representation (i.e. encoding methods) are proposed, which are applied on three different chromosome based evolutionary techniques, namely the Genetic Algorithm, the Bacterial Evolutionary Algorithm and the Particle Swarm Optimization method. Both representations are applied on the two former methods, whereas one of them is used for the latter optimization technique. Each mentioned algorithm is involved without and with local search steps as one of its evolutionary operators. Since the evolutionary operators of each technique are established according to the applied representation, this paper deals with a total number of ten different chromosome-based evolutionary methods. The obtained techniques are evaluated via simulation runs carried out on the well-known Taillard's benchmark problem set. Based on the experimental results the approaches for adapting chromosome based evolutionary methods are compared to each other.

Open Access: Yes

DOI: DOI not available

Minkowski's inequality based sensitivity analysis of fuzzy signatures

Ádám Bukovics István Harmati L. T. Koczy

Publication Name: Journal of Artificial Intelligence and Soft Computing Research

Publication Date: 2016-01-01

Volume: 6

Issue: 4

Page Range: 219-229

Description:

Fuzzy signatures were introduced as special tools to describe and handle complex systems without their detailed mathematical models. The input parameters of these systems naturally have uncertainties, due to human activities or lack of precise data. These uncertainties influence the final conclusion or decision about the system. In this paper we discuss the sensitivity of the weigthed general mean aggregation operator to the uncertainty of the input values, then we analyse the sensitivity of fuzzy signatures equipped with these aggregation operators. Finally, we apply our results to a fuzzy signature used in civil enginnering.

Open Access: Yes

DOI: 10.1515/jaiscr-2016-0016

On the sensitivity of the weighted relevance aggregation operator and its application to fuzzy signatures

István Harmati L. T. Koczy

Publication Name: Communications in Computer and Information Science

Publication Date: 2016-01-01

Volume: 611

Issue: Unknown

Page Range: 798-808

Description:

The weighted relevance aggregation operator is a modified, flexible version of the general power mean. In this paper we discuss the sensitivity of this operator, namely we give bounds on the change of the output in terms of vector norms of the change of the input variables. We apply these results to characterize to sensitivity of fuzzy signatures which are equipped with these operators in its nodes.

Open Access: Yes

DOI: 10.1007/978-3-319-40581-0_65

Applying fuzzy hough transform for identifying honed microgeometrical surfaces

Brigita Sziová Levente Solecki Balázs Sarkadi-Nagy L. T. Koczy Szilvia Nagy

Publication Name: Studies in Computational Intelligence

Publication Date: 2020-01-01

Volume: 819

Issue: Unknown

Page Range: 35-42

Description:

In the measurement of microgeometrical surfaces it is useful if the same location can be found on a surface for two or more different and independent measurements, as in this case not only statistical parameters of the measurements can be compared, but direct differences can be calculated. Honing is a typical surface processing method resulting in pattern consisting of straight valleys crossing at various angles. Honing pattern is of great help to find a special location. The main goal of this article is to find a method that is able to give some characteristic points that can be used for fitting two measured surfaces together. Hough transform is used in finding straight lines in an image or map, thus it could be used for determining crossing points of the honed surface. However, classical Hough transform either finds way too many disturbing lines in the case of a typical honed surface or almost none, depending on the parameter selection. To solve this rapid changing in the number of the resulting lines, we introduced fuzzy Hough transform. If a fuzzified version of the weights of the individual points in the Hough transform is used, the inverse of the transform becomes clearer, resulting in a pattern more suitable for finding the same location on two measured versions of a surface.

Open Access: Yes

DOI: 10.1007/978-3-030-16024-1_5

Three level modelling of uncertainties in the condition assessment of buildings

Ádám Bukovics István Harmati L. T. Koczy

Publication Name: Isciia 2016 7th International Symposium on Computational Intelligence and Industrial Applications

Publication Date: 2016-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Condition survey evaluation analyses (enginering-static expert reports) are often prepared about building structures (often focusing on load-bearing structures) in order to support appropriate maintenance and repair of the existing buildings. Based on these analyses modelling of the condition of buildings and building structures can be a big help to adopt decisions on intervention. In the course of our former research condition evaluation, decision support and ranking method was worked out which, based on a unified system of viewpoints, considering various priorities, is able to determine the condition of residential buildings. We have used tree-structure, fuzzy singleton signature based model, in which the expert specifies one discrete value for the condition of every examined building structure. In the course of our research it was experienced that the elaborated method is too subjective and uncertain, therefore the method is being further developed so that modelling of objective and subjective uncertainties become possible in the course of preparing expert opinions. Three levels were created to model uncertainties. Uncertainty on level 1 is how to transform verbal evaluations into fuzzy membership functions (verbal values cannot be unambiguously transformed into numerical values). In this model instead of membership values, which were used in the former model, we assign linguistic label modelling membership functions to the leaves of the structure. Level 2 we are modelling an uncertainty where even the expert is unable to precisely determine the condition of the examined structure. Often an interval is specified for the condition of the structure instead of a specific status value. It means that the condition of structure can have any value between two specified values with the same probability. To model it the triangular-shaped membership function is transformed into a trapezoidal-shaped membership function with the help of linguistic hedges. On level 3 it is modelled that the expert evaluation itself is not considered totally reliable. Subjectivity, professional preparedness of the expert, conducting the examination, or the quality of available circumstances and data may significantly influence the reliability of the final result. These uncertainties can be modelled by modifying the shapes of the membership function. The fuzzy set signature based model created by modelling the uncertainties at three levels is able to model with proper accuracy (more sophistically as compared to the former model) the condition of buildings, which were specified by verbal evaluation in expert opinion.

Open Access: Yes

DOI: DOI not available

On the convergence of fuzzy grey cognitive maps

István Harmati L. T. Koczy

Publication Name: Advances in Intelligent Systems and Computing

Publication Date: 2020-01-01

Volume: 945

Issue: Unknown

Page Range: 74-84

Description:

Fuzzy grey cognitive maps (FGCMs) are extensions of fuzzy cognitive maps (FCMs), applying uncertain weights between the concepts. This uncertainty is expressed by so-called grey numbers. Similarly to FCMs, the inference is determined by an iteration process, which may converge to an equilibrium point, but limit cycles or chaotic behaviour may also turn up. In this paper, based on the grey weighted connections between the concepts and the parameter of the sigmoid threshold function, we give sufficient conditions for the existence and uniqueness of fixed points for sigmoid FGCMs.

Open Access: Yes

DOI: 10.1007/978-3-030-18058-4_6

A rule-based expert system for automatic question classification in mathematics adaptive assessment on indonesian elementary school environment

Siti Rochimah Umi Laili Yuhana Alex Tormási Eko Mulyanto Yuniarno Aliia Rysbekova Mauridhi Hery Purnomo L. T. Koczy

Publication Name: International Journal of Innovative Computing Information and Control

Publication Date: 2019-02-01

Volume: 15

Issue: 1

Page Range: 143-161

Description:

This paper is part of research in developing a competency-based assessment system for mathematics in Indonesian elementary school environment. An essential task is to accurately classify questions based on competency and difficulty level. Thus, an expert system is needed to classify those questions since competency information is often manually defined by experts. The objectives of this work are replacing a human expert’s role in the related knowledge engineering process and providing a rule-based expert system to supersede an expert to classify the questions. Five types of the rule-based algorithm: OneR, RIPPER, PART, FURIA, and J48, were applied to the dataset, which is comprised of 9454 real mathematics examination questions collected from several Indonesian elementary schools. Following the knowledge engineering principles, these algorithms generated the classification rules based on a pattern of the data. The rules of the best performing algorithm were utilized by a knowledge base for inference. Finally, to be able to fully measure the system performance, ten expert teachers were involved in the question classification step. The results confirm that the system meets the stated objectives in classifying the competency and the difficulty level of a question automatically.

Open Access: Yes

DOI: 10.24507/ijicic.15.01.143

On the antecedent sets for fuzzy classification of colorectal polyps with stabilized KH interpolation

Ferenc Lilik L. T. Koczy Szilvia Nagy

Publication Name: Studies in Computational Intelligence

Publication Date: 2019-01-01

Volume: 796

Issue: Unknown

Page Range: 23-33

Description:

Polyps in the colorectal part of the bowel appear often, and in many cases these polyps can develop into malign lesions, such as cancer. Colonoscopy is the most efficient way to study the inner surface of the colorectum, and doctors usually are able to detect polyps on a motion picture diagnostic session. However, it is useful to have an automated tool that can help drawing attention to given parts of the image, and later a method for classification the polyps can also be developed. Statistical properties of the colour channels of the images are used as antecedents for a fuzzy decision system, together with edge densities and Renyi entropies-based structural entropy. However promising the processed images are, the variation in the preparation of the diagnosis as well as the practice of the operating personnel can lead to images with significantly different noise and distortion level, thus detecting the polyp can be complicated. In the following considerations image groups are presented that have similarities from the polyp detection point of view, and those type of images are also given, which can spoil a well prepared detecting system.

Open Access: Yes

DOI: 10.1007/978-3-030-00485-9_3

Intuitionistic Fuzzy Model of Traffic Jam Regions and Rush Hours for the Time Dependent Traveling Salesman Problem

P. Földesi Boldizsar Tuu-Szabo Ruba Almahasneh L. T. Koczy

Publication Name: Advances in Intelligent Systems and Computing

Publication Date: 2019-01-01

Volume: 1000

Issue: Unknown

Page Range: 123-134

Description:

The Traveling Salesman Problem (TSP) is one of the most extensively studied NP-hard graph search problems. Many researchers published numerous approaches for quality solutions, applying various techniques in order to find the optimum (least cost) or semi optimum solution. Moreover, there are many different extensions and modifications of the original problem, The Time Dependent Traveling Salesman Problem (TD TSP) is a prime example. TD TSP indeed was one of the most realistic extensions of the original TSP towards assessment of traffic conditions [1]. Where the edges between nodes are assigned different cost (weight), considering whether they are traveled during the rush hour periods or they cross the traffic jam regions. In such conditions edges are assigned higher costs [1]. In this paper we introduce an even more realistic approach, the IFTD TSP (Intuitionistic Fuzzy Time Dependent Traveling Salesman Problem); which is an extension of the classic TD TSP with the additional notion of intuitionistic fuzzy sets. Our core concept is to employ intuitionistic fuzzy sets of the cost between nodes to quantify traffic jam regions, and the rush hour periods. Since the intuitionistic fuzzy sets are generalizations of the original fuzzy sets [2], then our approach is a usefully extended, alternative model of the original abstract problem. By demonstrating the addition of intuitionistic fuzzy elements to quantify the intangible jam factors and rush hours, and creating an inference system that approximates the tour cost in a more realistic way [3]. Since our motivation is to give a useful and practical alternative (extension) of the basic TD TSP problem, the DBMEA (Discrete Bacterial Memetic Evolutionary Algorithm) was used in order to calculate the (quasi-)optimum or semi optimum solution. DBMEA has been proven to be effective and efficient in a wide segment of NP-hard problems, including the original TSP and the TD TSP as well [4]. The results from the runs based on the extensions of the family of benchmarks generated from the original TD TSP benchmark data set showed rather good and credible initial results.

Open Access: Yes

DOI: 10.1007/978-3-030-21920-8_12

A population based metaheuristic for traveling salesman type problems

P. Földesi Boldizsar Tuu-Szabo L. T. Koczy

Publication Name: 2017 International Conference on Fuzzy Theory and Its Applications Ifuzzy 2017

Publication Date: 2017-03-09

Volume: 2017-November

Issue: Unknown

Page Range: 1-5

Description:

In this paper we present a metaheuristic method, called DBMEA. It combines the bacterial evolutionary algorithm with local search techniques. Based on our test results it can be used for solving efficiently more discrete optimization problems. The algorithm was tested on Traveling Salesman Problem and Traveling Repairman Problem (TRP) benchmark instances found in the literature. In the case of TSP the DBMEA algorithm produced optimal or near-optimal solutions for all tested instances. Although the most efficient TSP solver method, the Helsgaun's Lin-Kernighan heuristic was faster than DBMEA, but in the case of DBMEA the runtime was more predictable than it the case of other methods. In the case of TRP the results are competitive in terms of accuracy and runtimes with the state-of-the art methods. Except two instances our algorithm found the best-known solutions, and for the biggest tested instance it found new best solution. The runtime was on average 30% faster than the most efficient heuristic in the literature.

Open Access: Yes

DOI: 10.1109/iFUZZY.2017.8311797

Some considerations on data mining from questionnaires by constructing fuzzy signatures based on factor analysis

D. Susniene Ojaras Purvinis L. T. Koczy

Publication Name: Journal of Intelligent and Fuzzy Systems

Publication Date: 2019-01-01

Volume: 36

Issue: 4

Page Range: 3739-3749

Description:

To interpret and to process the answers to questionnaires with large amount of questions may be not easy task. They are multidimensional data, sometimes with high dimensionality (in the hundreds). Therefore, it is necessary that some data reduction approach should be employed. On the other hand, answers to specific questions in questionnaires are imprecise, and the type and degree of imprecision is determined by the kind of the questions. The authors of the paper consider the imprecise answers to management type questions using a numerical scale as fuzzy degrees, and based on the semantic connections among the individual questions, a hierarchical structure is assumed. The paper suggests the use of factor analysis in order to determine this hierarchical structure, and thus the construction of fuzzy signatures from the tree graph representing the connections among the questions and answers, and the values normalized into membership degrees are assigned to the leaves of this tree. An interesting issue is how to determine the aggregations at the intermediate nodes. This may happen based on management science domain expert knowledge, and validated by the obtained results. Kohonen maps are used to demonstrate the clusters emerging among the overall fuzzy degrees representing the Fuzzy Signatures. The evaluation brings some results that partly confirm soft science based assumptions about employee behavior in the literature, and partly bring some interesting novel recognitions that may be brought in feedback to the original management science related problem, where the new method is illustrated.

Open Access: Yes

DOI: 10.3233/JIFS-18548

Wavelet based fuzzy rule bases in pre-qualification of access networks' wire pairs

Ferenc Lilik L. T. Koczy Szilvia Nagy

Publication Name: IEEE AFRICON Conference

Publication Date: 2015-11-18

Volume: 2015-November

Issue: Unknown

Page Range: Unknown

Description:

Even though the penetration of the fibre optical cables into telecommunication access networks seems to be accelerated, most of the customers are connected to the central office or to the telecommunication nodes by the copper wire pairs of the old telephone network. Until the replacement of the lines, their needs for modern high speed data communications services can be fulfilled by these symmetrical wire pairs. Equipment manufacturers produce equipments of the latest technologies for these networks (e.g. VDSL2), however pre-qualification of wire pairs of access networks is also essential, as the estimation of the performance gives the possibility to optimize the offered ensemble of services for telecommunications service providers. Our previous performance evaluation method based on fuzzy rule bases at discrete values of the insertion loss at 6 characteristic frequencies is improved by wavelet analysis. We have also proved, that the fine structure of the insertion loss spectrum does not play role in the achievable data transfer rate of the lines.

Open Access: Yes

DOI: 10.1109/AFRCON.2015.7332034

On wavelet based enhancing possibilities of fuzzy classification methods

Ferenc Lilik Brigita Sziová Levente Solecki L. T. Koczy Szilvia Nagy

Publication Name: Advances in Intelligent Systems and Computing

Publication Date: 2020-01-01

Volume: 945

Issue: Unknown

Page Range: 56-73

Description:

If the antecedents of a fuzzy classification method are derived from pictures or measured data, it might have too many dimensions to handle. A classification scheme based on such data has to apply a careful selection or processing of the measured results: either a sampling, re-sampling is necessary or the usage of functions, transformations that reduce the long, high dimensional observed data vector or matrix into a single point or to a low number of points. Wavelet analysis can be useful in such cases in two ways. As the number of resulting points of the wavelet analysis is approximately half at each filters, a consecutive application of wavelet transform can compress the measurement data, thus reducing the dimensionality of the signal, i.e., the antecedent. An SHDSL telecommunication line evaluation is used to demonstrate this type of applicability, wavelets help in this case to overcome the problem of a one dimensional signal sampling. In the case of using statistical functions, like mean, variance, gradient, edge density, Shannon or Rényi entropies for the extraction of the information from a picture or a measured data set, and they don not produce enough information for performing the classification well enough, one or two consecutive steps of wavelet analysis and applying the same functions for the thus resulting data can extend the number of antecedents, and can distill such parameters that were invisible for these functions in the original data set. We give two examples, two fuzzy classification schemes to show the improvement caused by wavelet analysis: a measured surface of a combustion engine cylinder and a colonoscopy picture. In the case of the first example the wear degree is to be determine, in the case of the second one, the roundish polyp content of the picture. In the first case the applied statistical functions are Rényi entropy differences, the structural entropies, in the second case mean, standard deviation, Canny filtered edge density, gradients and the entropies. In all the examples stabilized KH rule interpolation was used to treat sparse rulebases. The preliminary version of this paper was presented at the 3rd Conference on Information Technology, Systems Research and Computational Physics, 2–5 July 2018, Cracow, Poland [1].

Open Access: Yes

DOI: 10.1007/978-3-030-18058-4_5

Evaluation of waste management systems using fuzzy cognitive maps and optimization

F. Hatwágner P. Földesi A. Buruzs L. T. Koczy

Publication Name: 2015 10th Asian Control Conference Emerging Control Techniques for A Sustainable World Ascc 2015

Publication Date: 2015-09-08

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Integrated Waste Management Systems (IWMS) are very complex systems with a lot of uncertainty. These can be defined as the selection and application of suitable techniques, technologies and management programs to achieve waste management objectives and goals. In order to support the decision making process in waste management we propose the use of Fuzzy Cognitive Map (FCM) and Bacterial Evolutionary Algorithm (BEA) methods since the combination of the FCM and BEA seem to be suitable to model complex mechanisms such as IWMS. While the FCM is formed for a chosen system by determining the concepts and their relationships, it is possible to quantitatively simulate the system considering its parameters. However, if the time series of the factors of the system are known, then the connection matrix of FCM, thus the causal relations among the parameters can be determined by optimization. This way a more objective description of IWMS can be given.

Open Access: Yes

DOI: 10.1109/ASCC.2015.7244894

A memetic version of the bacterial evolutionary algorithm for discrete optimization problems

P. Földesi Boldizsar Tuu-Szabo L. T. Koczy

Publication Name: Advances in Intelligent Systems and Computing

Publication Date: 2020-01-01

Volume: 945

Issue: Unknown

Page Range: 44-55

Description:

In this paper we present our test results with our memetic algorithm, the Discrete Bacterial Memetic Evolutionary Algorithm (DBMEA). The algorithm combines the Bacterial Evolutionary Algorithm with discrete local search techniques (2-opt and 3-opt). The algorithm has been tested on four discrete NP-hard optimization problems so far, on the Traveling Salesman Problem, and on its three variants (the Traveling Salesman Problem with Time Windows, the Traveling Repairman Problem, and the Time Dependent Traveling Salesman Problem). The DBMEA proved to be efficient for all problems: it found optimal or close-optimal solutions. For the Traveling Repairman Problem the DBMEA outperformed even the state-of-the-art methods. The preliminary version of this paper was presented at the 3rd Conference on Information Technology, Systems Research and Computational Physics, 2–5 July 2018, Cracow, Poland [1].

Open Access: Yes

DOI: 10.1007/978-3-030-18058-4_4

Behavioral analysis of fuzzy cognitive map models by simulation

F. Hatwágner L. T. Koczy Vesa A. Niskanen

Publication Name: Ifsa Scis 2017 Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems

Publication Date: 2017-08-30

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Fuzzy Cognitive Maps (FCM) are widely applied to support decision making and for the prediction of the future behavior of systems. In this paper several real expert-defined models of an organization will be investigated. Simulations were performed in order to examine the asymptotic behavior of these models, especially to find (all) fixed point attractors, or to discover chaotic behavior. A sigmoid type of inference function was applied, and the effect of the steepness parameter on simulation results was investigated, too. It will be shown by several examples that the steepness parameter may even change the number and values of the final state vectors. In the end, the systematic study of the behavior of the models in terms of the changes of the (uncertain) relationship values among system components were studied.

Open Access: Yes

DOI: 10.1109/IFSA-SCIS.2017.8023345

Two-Stage Learning Based Fuzzy Cognitive Maps Reduction Approach

F. Hatwágner M. Furkan Dodurka Elpiniki I. Papageorgiou Leon Urbas L. T. Koczy Engin Yesil

Publication Name: IEEE Transactions on Fuzzy Systems

Publication Date: 2018-10-01

Volume: 26

Issue: 5

Page Range: 2938-2952

Description:

In this study, a new two-stage learning based reduction approach for fuzzy cognitive maps (FCM) is introduced in order to reduce the number of concepts. FCM is a graphical modeling technique that follows a reasoning approach similar to the human reasoning and the decision-making process. The FCM model incorporates the available knowledge and expertise in the form of concepts and in the direction and strength of the interactions among concepts. One of the modeling problems of FCMs is that oversized FCM models suffer from interpretability problems. An oversized FCM may contain concepts that are semantically similar and affect the other concepts in a similar way. This new study introduces a two-stage model reduction approach, and both static and dynamic analyses are considered without losing essential information. In the first stage, the number of concepts is reduced by merging similar concepts into clusters, whereas in the second stage the transformation function parameters of concepts are optimized. In order to show the benefit of using the proposed reduction approach, two sets of studies are conducted. First, a huge set of synthetic FCMs are generated, and the results of these statistical analyses are presented via various tables and figures. Subsequently, suggestions to the decision makers are given. Second, experimental studies are also presented to show the decision parameters and procedure for the proposed approach. The results show that after using the concept reduction approach presented in this study, the interpretability of FCM increases with an acceptable amount of information loss in the output concepts.

Open Access: Yes

DOI: 10.1109/TFUZZ.2018.2793904

Improvements on the Convergence and Stability of Fuzzy Grey Cognitive Maps

István Harmati L. T. Koczy

Publication Name: Communications in Computer and Information Science

Publication Date: 2020-01-01

Volume: 1239 CCIS

Issue: Unknown

Page Range: 509-523

Description:

Fuzzy grey cognitive maps (FGCMs) are extensions of fuzzy cognitive maps (FCMs), where the causal connections between the concepts are represented by so-called grey numbers. Just like in classical FCMs, the inference is determined by an iteration process, which may converge to an equilibrium point, but limit cycles or chaotic behaviour may also show up. In this paper, based on network measures like in-degree, out-degree and connectivity, we provide new sufficient conditions for the existence and uniqueness of fixed points for FGCMs. Moreover, a tighter convergence condition is presented using the spectral radius of the modified weight matrix.

Open Access: Yes

DOI: 10.1007/978-3-030-50153-2_38

Process of inversion in fuzzy interpolation model using fuzzy geometry

Suman Das L. T. Koczy Debjani Chakraborty

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2020-07-01

Volume: 2020-July

Issue: Unknown

Page Range: Unknown

Description:

Fuzzy rule interpolation (FRI) predicts an accountable outcome of a possible course of action in sparse fuzzy rule base system (FRBS). However, in real life, we encounter some situations where the antecedent has to be predicted to obtain a desired consequent of FRBS. In this situation, inverse fuzzy rule interpolation (IFRI) or backward fuzzy rule interpolation (BFRI) is used to get the desired outcome. Here a geometry based inverse fuzzy rule base interpolation (GIFRI) is suggested. The mathematical detail of the proposed method is elaborated and its geometrical interpretation is given with the help of fuzzy geometry. It is to be noted that the proposed method ensures that the inverse of the inverse is the original one.

Open Access: Yes

DOI: 10.1109/FUZZ48607.2020.9177698

Liver Cancer Classification Approach Using Yolov8

Belal Al-Khateeb Fatimah Ihsan Abdulsahib L. T. Koczy Szilvia Nagy

Publication Name: Lecture Notes in Networks and Systems

Publication Date: 2025-01-01

Volume: 1176 LNNS

Issue: Unknown

Page Range: 14-21

Description:

Liver cancer is a common and often fatal disorder that is becoming more commonplace worldwide. An accurate and timely diagnosis is necessary for both effective treatment and patient survival. In machine learning techniques, particularly deep learning, obtaining a large and diverse dataset is still a challenge for deep neural network training, particularly in the medical industry. This paper presents a classification of circulating tumor cells based on the YOLOv8 algorithm. Tumor cell identification and classification can be achieved by utilizing the algorithm’s multi-layer high-level stacking, weight sharing, local connection, and pooling characteristics. The goal is to design a liver cancer classification system that makes it easier and increases the efficiency of doctors in analyzing the results of liver cancer. The models show the absolute the accuracy is 100%, 100%, 98%, 96% to Yolov8n, Yolov8s, Yolov8m, and Yolov8l respectively.

Open Access: Yes

DOI: 10.1007/978-3-031-73997-2_2

Building renovation cost optimization with the support of fuzzy signature state machines

G. Molnárka L. T. Koczy

Publication Name: Advances in Intelligent Systems and Computing

Publication Date: 2015-01-01

Volume: 331

Issue: Unknown

Page Range: 129-138

Description:

The renovation of a significant segment of housing sector in Budapest, Hungary is overdue. Besides other causes, the absence of any effective tool that may support the decisions of the ownership communities in determining the technically verified steps and solutions in repair processes hinders the improvement of the physical condition of old residential houses. In this paper we propose a new formal method and approach for generating such tool that considers the costs and feasibilities of alternative renovation processes with professional data obtained from building diagnostics surveys, technical reports and contractors’ billing database. As a case study, a comprehensive renovation chain of the roof structure of a pre-war residential house will be evaluated.

Open Access: Yes

DOI: 10.1007/978-3-319-13153-5_13

Expert-Based Method of Integrated Waste Management Systems for Developing Fuzzy Cognitive Map

F. Hatwágner A. Buruzs L. T. Koczy

Publication Name: Studies in Fuzziness and Soft Computing

Publication Date: 2015-01-01

Volume: 319

Issue: Unknown

Page Range: 111-137

Description:

Movement towards more sustainable waste management practice has been identified as a priority in the whole of EU. The EU Waste Management Strategy's requirements emphasize waste prevention; recycling and reuse; and improving final disposal and monitoring. In addition, in Hungary the national waste strategy requires an increase in the household waste recycling and recovery rates. Integrated waste management system (IWMS) can be defined as the selection and application of suitable and available techniques, technologies and management programs to achieve waste management objectives and goals. In this paper, the concept of ‘key drivers’ are defined as factors that change the status quo of an existing waste management system in either positive or negative direction. Due to the complexity and uncertainty occurring in sustainable waste management systems, we propose the use of fuzzy cognitive map (FCM) and bacterial evolutionary algorithm (BEA) methods to support the planning and decision making process of integrated systems, as the combination of the FCM and BEA seem to be suitable to model complex mechanisms such as IWMS. Since the FCM is formed for a selected system by determining the concepts and their relationships, it is possible to quantitatively simulate the system considering its parameters. The goal of optimization was to find such a connection matrix for FCM that makes possible to generate the most similar time series. This way a more objective description of IWMS can be given. While the FCM model represents the IWMS as a whole, BEA is used for parameter optimization and identification. Based on the results, in the near future we intend to apply the systems of systems (SoS) approach to regional IWMS.

Open Access: Yes

DOI: 10.1007/978-3-319-12883-2_4

Application of self-organizing maps for technological support of droplet epitaxy

Mark Farkas Ákos Nemcsics Antal Ürmös Zoltán Farkas Tamás Sándor L. T. Koczy

Publication Name: Acta Polytechnica Hungarica

Publication Date: 2017-01-01

Volume: 14

Issue: 4

Page Range: 207-224

Description:

The subject of this paper is the self-organized grouping of droplet epitaxial III-V-based nano-structures. For the nano-structure grouping, our developed algorithm - called Quantum Structure Analyzer 1.0 - is used. The operation of this software is based on the principles of the Kohonen Self-Organizing Network. Here, three possibilities for nano-structured groupings are shown. On one hand, we examine the classification of nanostructures with Kohonen Self-Organizing Maps, on the other hand, fuzzy inference systems are applied for the same goal. In the case of the fuzzy methods two approaches are examined in detail. According to the first fuzzy inference approach, the shape factor is calculated from the size of nanostructures. According to the second fuzzy inference approach, the shape factor calculation is based on the controllable parameters of the growth process (eg. pressure and the temperature of the substrate).

Open Access: Yes

DOI: 10.12700/APH.14.4.2017.4.12

Modeling of Fuzzy Rule-base Algorithm for the Time Dependent Traveling Salesman Problem

P. Földesi Boldizsar Tuu-Szabo Ruba Almahasneh L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2019-06-01

Volume: 2019-June

Issue: Unknown

Page Range: Unknown

Description:

The Traveling Salesman Problem (TSP) is one of the most extensively studied NP-hard graph search problems. In the literature, there have been numerous published attempts, applying various approaches in order to find the optimum (least cost) or semi optimum solution. Time Dependent Traveling Salesman Problem (TD TSP) is one of the most sufficient extensions and modifications of the original TSP problem. In TD TSP the costs of edges between nodes varies, they are assigned higher cost in the traffic jam region, such as city center or during the rush hour periods. In this paper, we introduce an even more realistic approach, the 3FTD TSP (Triple Fuzzy Time Dependent Traveling Salesman Problem); a fuzzified model of the original TD TSP. The 3FTD TSP presents a variation of the TD TSP utilizing fuzzy values in the cost between two nodes (shops, cities, etc.), the geographical areas of the traffic jam region, and also the rush hour period. The goal is to give a practically useful and realistic alternative of the basic TD TSP problem. In order to calculate the (quasi-) optimum solution, the Discrete Bacterial Memetic Evolutionary Algorithm was used, since it has been proven to be rather efficient (and predictably) in a wide range of NP-hard problems, including the original TSP and the TD TSP as well. The results from the runs based on the extensions of the family of benchmarks generated from the original TD TSP benchmark data set showed rather good and credible initial results.

Open Access: Yes

DOI: 10.1109/FUZZ-IEEE.2019.8858853

Selection from a fuzzy signature database by Mamdani-algorithm

Katalin Tamás L. T. Koczy

Publication Name: Sami 2008 6th International Symposium on Applied Machine Intelligence and Informatics Proceedings

Publication Date: 2008-08-25

Volume: Unknown

Issue: Unknown

Page Range: 63-68

Description:

There are many complex, well structured problems, where a hierarchical structure within the data is present. This means, that one or several components of the structure are determined at a higher level by a sub-tree of other components. The concept of fuzzy signatures was introduced to help model these kinds of problems. The data set belonging to a problem has an arbitrary structure, but due to some missing components, the structures of the data may slightly differ. So that these data can be evaluated, aggregation operators are given for each node in the arbitrary structure for the purpose of modifying the structure. To deduce a conclusion for an observation from a data set having the structure mentioned above, fuzzy signature based rule bases and the generalisation of Mamdani-type inference were introduced. In this paper the formerly introduced idea of Mamdani-type inference in fuzzy signature based rule bases will be used for selecting records from an available data base which maximally match the requirements specified in a pattern. Finally a possible application on a realistic example with missing data components will be shown. © 2008 IEEE.

Open Access: Yes

DOI: 10.1109/SAMI.2008.4469135

Prioritisation of Nielsen’s usability heuristics for user interface design using fuzzy cognitive maps

Muhanna Muhanna Rita N. Amro Saransh Dhama L. T. Koczy

Publication Name: Communications in Computer and Information Science

Publication Date: 2018-01-01

Volume: 853

Issue: Unknown

Page Range: 511-522

Description:

Usability Heuristics are being widely used as a means of evaluating user interfaces. However, little existing work has been done that focused on assessing the effect of these heuristics individually or collectively on said systems. In this paper, the authors propose an approach to evaluating the usability of systems that deploys a prioritised version of Nielsen’s usability heuristics. Fuzzy cognitive maps were used to prioritise the original heuristics according to experts in both fields. Using either set of heuristics evaluators can identify the same number of usability issues. However, when trying to enhance the overall usability of a system, the prioritised set of heuristics can help stakeholders focus their limited resources on fixing the subset of issues that collectively has the worst effect on the usability of their systems during each iteration. To test the findings proposed by authors several websites were evaluated for various usability problems. The experimental results show that by using the proposed heuristics, evaluators were able to find a comparable number of problems to those who used Nielsen’s, the prioritised heuristics resulted in an ordered list of issues based on their effect on usability. Therefore, the authors believe that heuristic evaluation in general, and their introduced heuristics in particular, are effective in dealing with issues when facing situations of limited resources.

Open Access: Yes

DOI: 10.1007/978-3-319-91473-2_44

Fuzzy signature based methods for modelling the structural condition of residential buildings

Ádám Bukovics István Harmati L. T. Koczy

Publication Name: Studies in Fuzziness and Soft Computing

Publication Date: 2018-01-01

Volume: 357

Issue: Unknown

Page Range: 237-273

Description:

Conservation, extension or renovation of residential buildings is a task that requires intensive attention, where it must be ensured that design and construction works are carried out in proper quality. Priority is given to the proper use of the available financial resources. Incorrect assessment of renovation or reconstruction needs might cause considerable financial loss without implementing necessary interventions (which could eliminate eventual deteriorations, or hinder their reoccurrence).

Open Access: Yes

DOI: 10.1007/978-3-319-60207-3_16

On combination of wavelet transformation and stabilized KH interpolation for fuzzy inferences based on high dimensional sampled functions

Ferenc Lilik L. T. Koczy Szilvia Nagy

Publication Name: Studies in Computational Intelligence

Publication Date: 2018-01-01

Volume: 758

Issue: Unknown

Page Range: 31-42

Description:

A new approach for inference based on treating sampled functions is presented. Sampled functions can be transformed into only a few points by wavelet analysis, thus the complete function is represented by these several discrete points. The finiteness of the teaching samples and the resulting sparse rule bases can be handled by fuzzy rule interpolation methods, like KH interpolation. Using SHDSL transmission performance prediction as an example, the simplification of inference problems based on large, sampled vectors by wavelet transformation and fuzzy rule interpolation applied on these vectors are introduced in this paper.

Open Access: Yes

DOI: 10.1007/978-3-319-74681-4_3

Crime “hot-spots” identification and analysis in Hungary by computational intelligence

P. Földesi Boldizsar Tuu-Szabo Gábor Kovács Gergő Fogarasi L. T. Koczy Szilvia Nagy

Publication Name: Acta Polytechnica Hungarica

Publication Date: 2019-01-01

Volume: 16

Issue: 10

Page Range: 137-155

Description:

In the constantly growing and widening field of forensic science, crime maps are used in versatile ways. The representation of the data and analysis could offer some steps toward crime prevention and helps understand patterns, in terms of a timely distribution of crime types. Clustering is able to help identify criminal hot-spots and additional analysis may determine which areas require intervention. The aim of this study is to present an analysis of criminal information related to Hungary, in annual and monthly breakdown.

Open Access: Yes

DOI: 10.12700/APH.16.10.2019.10.9

Dynamic fuzzy rule weight optimization for a Fuzzy Based Single-Stroke Character Recognizer

Alex Tormási L. T. Koczy

Publication Name: Ines 2013 IEEE 17th International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2013-12-12

Volume: Unknown

Issue: Unknown

Page Range: 119-124

Description:

In this paper a dynamic fuzzy rule weighting method (DFW) combined with evolutionary optimization are presented for the formerly published Fuzzy Based Single-Stroke Character Recognizer (FUBAR) method. With the introduced rule weighting technique the consequent parts of the if...then... rules are calculated similarly to the original FUBAR method, but a dynamic fuzzy rule weight Wn([0,1]) described as a fuzzy set is applied to it in O n·1/Wn(On) form, where On is the output of the rule. The membership functions of DFW-s are determined by bacterial evolutionary algorithm. The paper compares the results of the proposed new algorithm with other (formerly published) FUBAR algorithms and also with other commercial and academic single-stroke recognizers in terms of recognition accuracy and computational resources needed. © 2013 IEEE.

Open Access: Yes

DOI: 10.1109/INES.2013.6632795

Discrete bacterial memetic evolutionary algorithm for the time dependent traveling salesman problem

P. Földesi Boldizsar Tuu-Szabo L. T. Koczy

Publication Name: Communications in Computer and Information Science

Publication Date: 2018-01-01

Volume: 853

Issue: Unknown

Page Range: 523-533

Description:

The Time Dependent Traveling Salesman Problem (TDTSP) that is addressed in this paper is a variant of the well-known Traveling Salesman Problem. In this problem the distances between nodes vary in time (are longer in rush hours in the city centre), Our Discrete Bacterial Evolutionary Algorithm (DBMEA) was tested on benchmark problems (on bier127 and on a self-generated problem with 250 nodes) with various jam factors. The results demonstrate the effectiveness of the algorithm.

Open Access: Yes

DOI: 10.1007/978-3-319-91473-2_45

Simulations of higher-order protein organizations using a fuzzy framework

Boldizsar Tuu-Szabo M. Fuxreiter L. T. Koczy

Publication Name: Complexity

Publication Date: 2018-01-01

Volume: 2018

Issue: Unknown

Page Range: Unknown

Description:

Spatiotemporal regulation of the biochemical information is often linked to supramolecular organizations proteins and nucleic acids, the driving forces of which have yet to be elucidated. Although the critical role of multivalency in phase transition has been recognized, the organization principles of higher-order structures need to be understood. Here, we present a fuzzy mathematical framework to handle the heterogeneity of interactions patterns and the resultant multiplicity of conformational states in protein assemblies. In this model, redundant binding motifs can establish simultaneous and partial interactions with multiple targets. We demonstrate that these multivalent, weak contacts facilitate polymer formation, while recapitulating the observed valency-dependence. In addition, the impact of linker dynamics and motif binding affinity, as well as the interplay between the two effects was studied. Our results support that fuzziness is a critical factor in driving higher-order protein organizations, and this could be used as a general framework to simulate different kinds of supramolecular assemblies.

Open Access: Yes

DOI: 10.1155/2018/6360846

Comparative Analysis of Machine Learning Algorithms in Traffic Mainstream Control on Freeway Networks

Mehran Amini L. T. Koczy

Publication Name: Ines 2024 28th IEEE International Conference on Intelligent Engineering Systems 2024 Proceedings

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: 37-41

Description:

Efficient management of mainstream traffic flow on freeway networks is a critical challenge in urban transportation, with significant implications for congestion mitigation and environmental sustainability. The purpose of this study is to address the problem of predicting traffic volumes and maintaining flow rates below critical densities, thereby preventing the onset of congestion on interconnected freeway systems. Motivated by the need for real-Time traffic control strategies, this research employs machine learning algorithms to forecast traffic volumes, leveraging a comprehensive dataset of traffic patterns on freeways. In our approach, we conducted a comparative analysis of two advanced machine learning algorithms: Long Short-Term Memory (LSTM) networks, which are adept at modeling time-series data with long-range temporal dependencies, and Random Forest regression, known for its robust performance across diverse datasets. We enriched the traffic data through feature engineering, incorporating temporal variables, vehicular counts, and a calculated measure of proximity to critical density for the targeted freeway. Our findings indicate a markedly disparate performance between the algorithms. The LSTM model showed a moderate ability to capture the variance in traffic flow, with an R2 score of 0.619. In contrast, the Random Forest model demonstrated exceptional predictive accuracy, achieving an R2 of 0.998, and substantially outperforming the LSTM model in terms of both Mean Squared Error and Root Mean Squared Error.

Open Access: Yes

DOI: 10.1109/INES63318.2024.10629114

Advanced learning of fuzzy cognitive maps of waste management by bacterial algorithm

F. Hatwágner R. C. Pozna A. Buruzs L. T. Koczy

Publication Name: Proceedings of the 2013 Joint Ifsa World Congress and NAFIPS Annual Meeting Ifsa NAFIPS 2013

Publication Date: 2013-10-31

Volume: Unknown

Issue: Unknown

Page Range: 890-895

Description:

Fuzzy cognitive maps (FCMs) are a very convenient and simple tool for modeling complex systems. They are popular due to their simplicity and user friendliness. However, according to [1], human experts are subjective and can handle only relatively simple networks therefore there is an urgent need to develop methods for automated generation of FCM models. The present research deals with the methodology of FCMs in combination with the Bacterial Evolutionary Algorithm (BEA). The method of FCMs using BEA seems to be suitable to model such complex mechanisms as integrated municipal waste management (IMWM) systems. This paper is an attempt to assess the sustainability of the IMWM system by investigating the FCM methodology based on the BEA with a holistic approach. As a result, the best scenario to an IMWM system can be assigned. © 2013 IEEE.

Open Access: Yes

DOI: 10.1109/IFSA-NAFIPS.2013.6608518

Classification of plantar foot alterations by fuzzy cognitive maps against multi-layer perceptron neural network

F. Hatwágner Antonio Hernández Zavala Silvia L. Chaparro-Cardenas Julian Andres Ramirez-Bautista L. T. Koczy Jorge A. Huerta-Ruelas

Publication Name: Biocybernetics and Biomedical Engineering

Publication Date: 2020-01-01

Volume: 40

Issue: 1

Page Range: 404-414

Description:

Load distribution analysis on foot surface allows knowing human mechanical behavior and aids the doctor in the detection of gait disorders like, the risk of foot ulcerations, leg discrepancy, and footprint alterations. Plantar pressure data combined with techniques that use integral reasoning produce easy understanding medical tools for assisting in treatment, early detection, and the development of preventive strategies. The present research compares the classification of human plantar foot alterations using Fuzzy Cognitive Maps (FCM) trained by Genetic Algorithm (GA) against a Multi-Layer Perceptron Neural Network (MLPNN). One hundred and fifty-one subject volunteers (aged 7–77) were classified previously with the flat foot (n = 70) and cavus foot (n = 81) by specialized physicians of the Piédica diagnostic center. The trial walking was conducted using plantar pressure platforms FreeMed®. The foot surface was divided into 14 areas that included toe 1 st to 5th, metatarsal joint 1st to 5th, lateral midfoot, medial midfoot, lateral heel, and medial heel. Pressure data were normalized for each area. Better performance in the classification using small amounts of data were found by using Fuzzy rather than non-Fuzzy approach.

Open Access: Yes

DOI: 10.1016/j.bbe.2019.12.008

Modeling the condition of buildings by real fuzzy sets

Ádám Bukovics L. T. Koczy

Publication Name: International Journal for Housing Science and Its Applications

Publication Date: 2014-02-13

Volume: 38

Issue: 1

Page Range: 1-12

Description:

It is an important task to qualify and rank residential buildings based on various priority aspects and to make optimum allocation of the material resources available for the renewal of the buildings. To this end a model based on fuzzy logic was prepared. To construct and to test this model many detailed technical-static expert reports were available all related to a stock of residential buildings in Budapest. Based on this report a database was created. With the help of this database a model was prepared, calculating a so-called status characteristic value between 0 and 1 on the basis of the structures and status of the buildings. For this calculation a fuzzy singleton signature model was prepared. Based on this a hierarchy can be set up related to the stock of buildings, which is suitable for supporting the decision-making on intervention. The model was examined by using the created database. Membership values characterising the status of the load-bearing structures - were defined on the basis of the deterioration of the structures. In this paper a new method for the determination of the membership values is described, which in addition to the deteriorations of the structures takes into account other parameters of the structures, and the impact exerted on the quality of the structure, too. The method is suitable for the determination of the membership values of all primary and secondary structures. As an example the membership values of the foundation structures of the buildings in the database were defined and the results were analysed. The method was elaborated by the use of 'real fuzzy values' (R-fuzzy sets), an extension of the concept of classic fuzzy sets, the former being suitable for simultaneously taking into account various aspects text. Copyright©2014 IAHS.

Open Access: Yes

DOI: DOI not available

Synergies between Fuzzy Signatures and Hypergraphs

Csaba Hajdu Ahmet Mehmet Karadeniz L. T. Koczy

Publication Name: Proceedings of the International Symposium on Applied Machine Intelligence and Informatics Sami

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: 495-500

Description:

Fuzzy signatures have demonstrated effectiveness in various knowledge-representation domains, including medical decision-making systems and complex decision-making tasks across numerous fields. Even though the advancements in the field of fuzzy signatures have been substantial, the complete potential for developing a comprehensive graph-theoretical description format for this domain still needs to be fully realized. This paper introduces a novel hypergraph-based method for modeling fuzzy signatures, which offers a structured approach to their representation but also showcases the potential synergy between fuzzy signatures and hypergraphs. The proposed method is designed to improve fuzzy information representation and streamline the aggregation-based decision-making process. Future research is anticipated to extend the applicability of this method to control systems and robotics. Furthermore, the hypergraph-based model opens new avenues for the algebraic analysis of fuzzy signatures through tensor-based representations.

Open Access: Yes

DOI: 10.1109/SAMI63904.2025.10883273

Fuzzy based hierarchical performance evaluation in telecommunications access networks

Ferenc Lilik L. T. Koczy

Publication Name: 2014 International Conference on Humanoid Nanotechnology Information Technology Communication and Control Environment and Management Hnicem 2014 7th Hnicem 2014 Joint with 6th International Symposium on Computational Intelligence and Intelligent Informatics Co Located with 10th Erdt Conference

Publication Date: 2014-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Performance evaluation of wire pairs of telecommunications access networks is a great challenge for telecommunications service providers. Although there are existing methods and systems for it, these are expensive or unpunctual. This paper presents a novel, hierarchical fuzzy inference based performance evaluation method for wire pairs of access networks, which is based on measurements of the pairs. The set of antecedent (input) parameters and their role in the evaluation, the consequent (output) states and the type of the used fuzzy rule bases are presented. In addition, the behavior and the role of the noise that can be measured in the wire pairs are detailed.

Open Access: Yes

DOI: 10.1109/HNICEM.2014.7016242

Fuzzy signature structure-based finite-state machines in a residential building renovation procedure

G. Molnárka L. T. Koczy

Publication Name: Civil Comp Proceedings

Publication Date: 2014-01-01

Volume: 105

Issue: Unknown

Page Range: Unknown

Description:

Twenty years after the transition to the market-based housing sector the overall physical condition of pre-war urban-type residential houses remained below standard in Hungary. Among other factors, the fragmented ownership structure (at present, the capital-scarce former tenants constitute the stakeholders' community), and the given physical condition of the residential houses has resulted in difficulties in maintenance and repair. The options in the renovation process are limited by financial capabilities, however, the essential problem with maintenance originates from the unprofessional approach in decision-making. Although several decision-support tools exist that may help the stakeholders' communities, some properties of these tools make them unsuitable, or, as in the case of the facility management systems, their application may result in oversized expenses with needless functions. As a combination of the fuzzy signature structure and the principles of finite-state machines a new formal method is proposed for generate a tool for the supporting stakeholders' decisions in the building rehabilitation process, concerning necessity, cost efficiency and quality. With the support of information obtained from building diagnostic surveys, technical guides and contractors' billing databases an optimized renovation protocol is proposed.

Open Access: Yes

DOI: DOI not available

S-shaped fuzzy flip-flops

Rita Lovassy L. T. Koczy

Publication Name: 8th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics Cinti 2007

Publication Date: 2007-12-01

Volume: Unknown

Issue: Unknown

Page Range: 383-391

Description:

The multilayer perceptron is an artificial neural network that learns nonlinear function mappings. Nonlinear functions can be represented by multilayer perceptrons with units that use nonlinear activation functions. The neurons in the multilayer perceptron networks typically employ sigmoidal activation function. The next state of the J-K fuzzy flipflops (F3) using Fodor, Yager and Dombi operators present S-shaped characteristics. An interesting aspect of F3-s might be that they have a certain convergent behavior when one of their inputs (e.g. J) is exited repeatedly. If J is considered the equivalent of the traditional input of a neuron (with an adder unit applied before J), K might play a secondary modifier's role, or can just be set fix. The paper proposes the investigation of such possible F3-networks as new alternative types of neural networks.

Open Access: Yes

DOI: DOI not available

Increasing diagnostic accuracy by meta optimization of fuzzy rule bases

J. Botzheim Mario Drobics L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2007-12-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

In medicine the decision on which test to choose for a given decision problem is a delicate problem. On the one hand a positive test should be a reliable indicator on the presence of a disease, while on the other hand a negative test is required to be an indicator on the absence of a disease. Of course, these two goals are conflicting and a balanced decision according to the current situation is required. Inductive learning methods for (fuzzy) rule bases are, however, typically not capable of optimizing such complex and problem depending goal functions. We therefore present a meta-learning algorithm which selects a subset from a previously generated set of fuzzy rules using bacterial evolutionary algorithms. We also present a study where the proposed method is used to generate a model for predicting the presence/absence of hepatitis, based on laboratory results. © 2007 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2007.4295377

The effect of wavelet analyis on entropy based fuzzy classification of colonoscopy images

Brigita Sziová L. T. Koczy Szilvia Nagy

Publication Name: Iwaciii 2017 5th International Workshop on Advanced Computational Intelligence and Intelligent Informatics

Publication Date: 2017-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Colorectal polyp detection is important in preventing cancer. Structural entropy can detect different structures of distributions, such as image pixel brightness. Wavelet analysis can help in separating large-scale and fine resolution behaviour. In the method presented in this paper, the colonoscopy images are separated into segments, and a classification scheme is built in order to determine, whether there is a polyp part in the image segment or not. Without wavelet analysis edge density and structural entropy can be a basis of fuzzy classification for the polyp content of only good quality colonoscopy images, and still has about 10 percent false classification. In this contribution the effect of wavelet analysis on the classification scheme is studied.

Open Access: Yes

DOI: DOI not available

Evaluating the life quality of the built environment by FRI method

Sz Kovacs G. Molnárka L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2015-11-25

Volume: 2015-November

Issue: Unknown

Page Range: Unknown

Description:

The fuzzy rule interpolation (FRI) and the fuzzy signature methodology was successfully adapted for expressing the building condition. In this paper we extend this concept for estimating the life quality of the built environment, especially of the residential segment. The applied methodology is based on a hierarchical FRI as a straightforward implementation of the fuzzy signature concept. The paper also introduces some application details of a case study related to residential houses located in a historic district of Budapest, Hungary.

Open Access: Yes

DOI: 10.1109/FUZZ-IEEE.2015.7338029

A fuzzy information propagation algorithm for social network based recommender systems

Gergely Posfai Gabor Magyar L. T. Koczy

Publication Name: Advances in Intelligent Systems and Computing

Publication Date: 2017-01-01

Volume: 462

Issue: Unknown

Page Range: 35-49

Description:

Web-based services that have become prevalent in people’s everyday life generate huge amounts of data, which makes it hard for the users to search and discover interesting information. Therefore, tools for selecting and delivering personalized contents for users are crucial components of modern web applications. Social recommender systems suggest items to users assuming the knowledge of the users’ social network. This new approach can alleviate the common weaknesses of traditional recommender systems, which completely ignore the users’ personal relationships in the recommendation process. In this paper, a social network based fuzzy recommendation technique is presented, which propagates information through the users’ social network and predicts how users would probably like a certain product in the future. Experimental results on a public dataset show that the proposed method can significantly outperform popular and widely used recommendation system methods in terms of recommendation coverage while maintaining prediction accuracy and performs especially well for cold start users, that have only rated a few items or no item at all previously.

Open Access: Yes

DOI: 10.1007/978-3-319-44260-0_3

Banking applications of FCM models

F. Hatwágner Gyula Vastag L. T. Koczy Vesa A. Niskanen

Publication Name: Studies in Computational Intelligence

Publication Date: 2019-01-01

Volume: 796

Issue: Unknown

Page Range: 61-72

Description:

Fuzzy Cognitive Map (FCMs) is an appropriate tool to describe, qualitatively analyze or simulate the behavior of complex systems. FCMs are bipolar fuzzy graphs: their building blocks are the concepts and the arcs. Concepts represent the most important components of the system, the weighted arcs define the strength and direction of cause-effect relationships among them. FCMs are created by experts in several cases. Despite the best intention the models may contain subjective information even if it was created by multiple experts. An inaccurate model may lead to misleading results, therefore it should be further analyzed before usage. Our method is able to automatically modify the connection weights and to test the effect of these changes. This way the hidden behavior of the model and the most influencing concepts can be mapped. Using the results the experts may modify the original model in order to achieve their goal. In this paper the internal operation of a department of a bank is modeled by FCM. The authors show how the modification of the connection weights affect the operation of the institute. This way it is easier to understand the working of the bank, and the most threatening dangers of the system getting into an unstable (chaotic or cyclic state) can be identified and timely preparations become possible.

Open Access: Yes

DOI: 10.1007/978-3-030-00485-9_7

Fuzzy single-stroke character recognizer with various rectangle fuzzy grids

Alex Tormási L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2014-02-03

Volume: 530

Issue: Unknown

Page Range: 145-159

Description:

In this chapter we introduce the results of a formerly published FUBAR character recognition method with various fuzzy grid parameters. The accuracy and efficiency of the handwritten single-stroke character recognition algorithm with different sized rectangle (N×M) fuzzy grids are investigated. The results are compared to other modified FUBAR algorithms and known commercial and academic recognition methods. Possible applications and further extensions are also discussed. This work is the extended and fully detailed version of a previously published abstract. © Springer International Publishing Switzerland 2014.

Open Access: Yes

DOI: 10.1007/978-3-319-03206-1_11

On the existence and uniqueness of fixed points of fuzzy cognitive maps

F. Hatwágner István Harmati L. T. Koczy

Publication Name: Communications in Computer and Information Science

Publication Date: 2018-01-01

Volume: 853

Issue: Unknown

Page Range: 490-500

Description:

Fuzzy Cognitive Maps (FCMs) are decision support tools, which were introduced to model complex behavioral systems. The final conclusion (output of the system) relies on the assumption that the system reaches an equilibrium point (fixed point) after a certain number of iteration. It is not straightforward that the iteration leads to a fixed point, since limit cycles and chaotic behaviour may also occur. In this article, we give sufficient conditions for the existence and uniqueness of the fixed point for log-sigmoid and hyperbolic tangent FCMs, based on the weighted connections between the concepts and the parameter of the threshold function. Moreover, in a special case, when all of the weights are non-negative, we prove that fixed point always exists, regardless of the parameter of the threshold function.

Open Access: Yes

DOI: 10.1007/978-3-319-91473-2_42

Hierarchical-interpolative fuzzy system construction by genetic and bacterial memetic programming approaches

Krisztián Balázs L. T. Koczy

Publication Name: International Journal of Uncertainty Fuzziness and Knowldege Based Systems

Publication Date: 2012-01-01

Volume: 20

Issue: SUPPL. 2

Page Range: 105-131

Description:

In this paper a family of new methods are proposed for constructing hierarchical-interpolative fuzzy rule bases in the frame of a fuzzy rule based supervised machine learning system modeling black box systems defined by input-output pairs. The resulting hierarchical rule base is constructed by using structure building pure evolutionary and memetic techniques, namely, Genetic and Bacterial Programming Algorithms and their memetic variants containing local search steps. Applying hierarchical-interpolative fuzzy rule bases is a rather efficient way of reducing the complexity of knowledge bases, whereas evolutionary methods (including memetic techniques) ensure a relatively fast convergence in the learning process. As it is presented in the paper, by applying a newly proposed representation schema these approaches can be combined to form hierarchical-interpolative machine learning systems. © 2012 World Scientific Publishing Company.

Open Access: Yes

DOI: 10.1142/S021848851240017X

Developing fuzzy cognitive maps for modeling regional waste management systems

R. C. Pozna A. Buruzs L. T. Koczy

Publication Name: Civil Comp Proceedings

Publication Date: 2013-01-01

Volume: 103

Issue: Unknown

Page Range: Unknown

Description:

Sustainable waste management systems necessarily include environmental, economic, social, institutional, legal and technical aspects. As a result of the incompleteness and multiple uncertainties occurring in sustainable waste management systems, we propose the use of fuzzy cognitive maps (FCM) to support the planning and decision making process. It is obvious that uncertainties involved with waste management represent vagueness rather than probability. Fuzzy sets and fuzzy logic are suitable to construct a formal description and a mathematically manageable model of systems and processes with such uncertainties. In the research described in this paper the FCM model of the Gyor RWMS is established and implemented in such a structure that its parameters and weights were flexibly variable. By observation of the model and its time dependent behaviour we determined under what conditions the long-term sustainability of a regional waste management system could be ensured. In this paper, the interpretation of the results obtained by the FCM model for the actual waste management system are presented. ©Civil-Comp Press, 2013.

Open Access: Yes

DOI: DOI not available

Fuzzy Decision Support Methodology for Sustainable Packaging System Design

A. Buruzs Dániel Pup Kata Vöröskoi L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2022-01-01

Volume: 955

Issue: Unknown

Page Range: 163-173

Description:

The aim of the present paper is to develop an integrated method that provides assistance to decision makers during packaging system planning, design, operation and evaluation from an environmental perspective. The role of the packaging system is to provide a cover for the handling and communication functions surrounding the product. Single-use and reusable packaging are known based on the time it participates in the goods trade. The purpose of the authors is to develop an evaluation model for the selection of packaging systems from an environmental and sustainability point of view in the supply chain.

Open Access: Yes

DOI: 10.1007/978-3-030-88817-6_19

The effect of image feature qualifiers on fuzzy colorectal polyp detection schemes using KH interpolation - Towards hierarchical fuzzy classification of coloscopic still images

Brigita Sziová L. T. Koczy Szilvia Nagy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2018-10-12

Volume: 2018-July

Issue: Unknown

Page Range: Unknown

Description:

Previous studies showed that intensities, intensity variation, edge densities, structural entropies of colonoscopy images and their wavelet transforms are good candidates for being selected as antecedents in fuzzy decision methods using KH interpolation for determining whether an image segment contains colorectal polyp segment. In the present consideration, we check which possible antecedent dimensions need interpolation, whether the average and variation of the gradients makes the classification more effective and whether some of the features can be omitted for some classes of images. The method is tested on three available databases consisting of images of three different resolutions, and according to the results, different resolutions, different types of polyps require different classification schemes, thus a hierarchical decision system needs to be built.

Open Access: Yes

DOI: 10.1109/FUZZ-IEEE.2018.8491479

Detection of Human Footprint Alterations by Fuzzy Cognitive Maps Trained with Genetic Algorithm

F. Hatwágner Antonio Hernández Zavala Silvia L. Chaparro-Cardenas Julian Andres Ramirez-Bautista L. T. Koczy Jorge A. Huerta-Ruelas

Publication Name: Proceedings of the Special Session 2018 17th Mexican International Conference on Artificial Intelligence Micai 2018

Publication Date: 2018-10-01

Volume: Unknown

Issue: Unknown

Page Range: 32-38

Description:

Mobility is an important part of our daily life, hence the good health of our lower extremities is essential. Gait analysis using kinetic data along with medical Decision Support System or Computer Aided Diagnosis provide to physicians support in gait disorder detection, the risk of foot ulcerations especially in diabetic patients, leg discrepancy, footprint pathologies, and many other applications in biomedical diagnosis. To increase confidence in the system, it is necessary to use a technique which uses a comprehensive reasoning and provide explanations to discover new relationships and combination of features. The present research is an attempt to assess the viability of investigating human footprint alterations using Fuzzy Cognitive Maps (FCM) combined with a Genetic Algorithm (GA), and it is part for preparation of investigating more efficient algorithms in the future. In the proposed method, GA is used to learn the weight matrix of an FCM model applied to identify alterations in the human footprint. Using historical plantar pressure data obtained by electronic platforms, combined with FCM and optimization algorithm, a promising outcome is presented in the field of Computer-Aided Diagnosis.

Open Access: Yes

DOI: 10.1109/MICAI46078.2018.00013

The line noise as the optional antecedent parameter of performance evaluation

Ferenc Lilik L. T. Koczy

Publication Name: Cinti 2012 13th IEEE International Symposium on Computational Intelligence and Informatics Proceedings

Publication Date: 2012-12-01

Volume: Unknown

Issue: Unknown

Page Range: 427-431

Description:

Performance evaluation of telecommunication lines can be a decisive action in the practice of telecommunication service providers. There are several evaluation techniques in use of telecommunication companies. These techniques can be divided into some groups depending on the efficiency, the cost or the set of the input parameters. This paper lists some of the used evaluation techniques, aims to shortly introduce a new method for preliminary evaluation of the twisted pairs of the access networks for commonly used digital data transmission technologies, and describe the circumstances of the line noise as an optional input parameter of decision making. It will be cleared, that the line noise plays role on forming data transfer rate, however in certain cases it can be passed over. © 2012 IEEE.

Open Access: Yes

DOI: 10.1109/CINTI.2012.6496804

Entropy based fuzzy classification and detection aid for colorectal polyps

Ferenc Lilik L. T. Koczy Szilvia Nagy

Publication Name: 2017 IEEE AFRICON Science Technology and Innovation for Africa AFRICON 2017

Publication Date: 2017-11-03

Volume: Unknown

Issue: Unknown

Page Range: 78-82

Description:

Colorectal polyps affect a large percentage of the population all over the world, and they can be a basis for more serious conditions such as cancers. As the most reliable method for detecting a polyp in the lower bowel tract is colonoscopy, more and more image processing experiments appear that help to find or characterize such a lesion. The social benefit of such methods is clear, any aid in detecting pre-cancer states saves lives. In the present considerations a fuzzy decision method for finding polyps on a colonoscopy image is presented. As a first step, the image taken during the colonoscopy is cut into tiles of size N by N, thus a rough localization of the lesion within the picture is also possible. The antecedent dimensions consist of statistical characteristics of the colour channels of the tiles, their Renyi entropies, edge density and fitted polynomial coefficients. The method's dependence on the tile-size within the images are also studied, and the success rate increases with the decrease of the tile size between 70 by 70 and 20 by 20 tile sizes.

Open Access: Yes

DOI: 10.1109/AFRCON.2017.8095459

Extended fuzzy signature based model for qualification of residential buildings

Ádám Bukovics Gergő Fogarasi L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2020-01-01

Volume: 819

Issue: Unknown

Page Range: 91-97

Description:

Residential buildings can be qualified and ranked based on many viewpoints. For the intervening decision-supporting survey of old residential buildings in the course of our former researches we have created a fuzzy signature based model which defines status evaluation and ranking of buildings on the basis of the condition of load-bearing structures and other building structures. We have extended and changed this model in a way so that it should take into account other viewpoints, too, which, in addition to the load bearing viewpoints strongly influence the manner of intervening. Since in addition to the importance of the given structure the relevance of the building structures of residential buildings are determined also by their quantities and other features, in our case it was necessary to determine relative and absolute relevance weights. We use a structure of fuzzy signature with variable aggregations, where the definition of aggregations is made by parameters, and the value of parameters are changing depending on the specific application, which follow the changes of relevance of given subtrees. The developed method is examined on the basis of a database for which we were used status evaluating expert reports relating to real stock of residential buildings.

Open Access: Yes

DOI: 10.1007/978-3-030-16024-1_12

Enhanced discrete bacterial memetic evolutionary algorithm - An efficacious metaheuristic for the traveling salesman optimization

P. Földesi Boldizsar Tuu-Szabo L. T. Koczy

Publication Name: Information Sciences

Publication Date: 2018-09-01

Volume: 460-461

Issue: Unknown

Page Range: 389-400

Description:

In this paper we present a novel universal metaheuristic, Discrete Bacterial Memetic Evolutionary Algorithm (DBMEA), which is based on the combination of the Bacterial Evolutionary Algorithm and local search techniques, used for solving NP-hard optimization problems. The algorithm was tested on a series of symmetric Traveling Salesman Problems (TSP) and Traveling Salesman Problem with time windows (TSPTW) benchmarks. The size of the symmetric TSP benchmarks went up to 5 000 cities. In all cases the DBMEA algorithm produced optimal or near-optimal solutions and the difference from the known best values was within 0.16%. While for large size problems it was much faster than the Concorde solver, it was found to be slower compared to the Helsgaun-Lin-Kernighan heuristic, which is the most efficient TSP solver method. With some slight modifications the same algorithm was also tested on TSP with time windows (TSPTW) benchmark instances. In most cases the DBMEA procedure found the known best solutions, and it was again the second fastest method compared with the state-of-the-art techniques for the TSPTW. DBMEA is called efficacious because it is a universal method. It can be efficiently applied to various NP-hard optimization problems and, as in all cases, it results in the optimal or a very near-optimal solutions, while its runtime is very predictable in terms of the size of the problem, and the topology of the instance does not affect its runtime significantly. Even though heuristics developed for a particular type of problem might perform better for that restricted class, our novel method proposed here is universally applicable and may be deployed successfully for optimizing other discreet NP-hard graph search and optimization problems as well.

Open Access: Yes

DOI: 10.1016/j.ins.2017.09.069

Improving the efficiency of a fuzzy-based single-stroke character recognizer with hierarchical rule-base

Alex Tormási L. T. Koczy

Publication Name: Cinti 2012 13th IEEE International Symposium on Computational Intelligence and Informatics Proceedings

Publication Date: 2012-12-01

Volume: Unknown

Issue: Unknown

Page Range: 421-426

Description:

In this paper we present an improved version of the fuzzy based single-stroke character recognizer introduced in previous works. The modified recognition method is able to reach an acceptable accuracy in the character recognition with a significant decrease on the computational complexity of the algorithm. Different hierarchical rule-base techniques were successfully used to improve the efficiency of fuzzy systems. The altered recognizer reached 98.82% average recognition rate with 26 different single-stroke symbols (based on Palm's Graffiti alphabet) without learning user-specific parameters or modifying the rule-base during the tests. The new algorithm has a small decrease in the recognition rate compared to the accuracy of the original systems but the new method has less computational price than the original system does. © 2012 IEEE.

Open Access: Yes

DOI: 10.1109/CINTI.2012.6496803

New parameterizable search space narrowing technique for adjusting between accuracy and interpretability in fuzzy systems

Krisztián Balázs L. T. Koczy

Publication Name: Cinti 2012 13th IEEE International Symposium on Computational Intelligence and Informatics Proceedings

Publication Date: 2012-12-01

Volume: Unknown

Issue: Unknown

Page Range: 323-328

Description:

It is well known that beyond the fact that fuzzy systems have favorable modeling capabilities from the viewpoint of accuracy, they also have outstanding inherent interpretability possibilities, which is a rather unique property among modeling architectures and which is a strong motivation for their research and application. This paper focuses on both mentioned property types and proposes a new technique for adjusting between accuracy and interpretability in modeling systems where fuzzy rule based architectures together with evolutionary algorithms are used for knowledge extraction. First, an inconsistency problem of conventional interpretable fuzzy systems is resolved. Then, a new search space narrowing technique for evolutionary algorithms is proposed, which can be applied for constructing interpretable fuzzy rule bases. Finally, the favorable properties of this new approach will be verified experimentally by carrying out simulation runs. © 2012 IEEE.

Open Access: Yes

DOI: 10.1109/CINTI.2012.6496783

Evaluating condition of buildings by applying fuzzy signatures and R-fuzzy operations

Ádám Bukovics L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2014-02-03

Volume: 530

Issue: Unknown

Page Range: 45-57

Description:

It is an significant task to qualify and rank residential buildings based on various priority aspects and to make optimum allocation of the material resources available for the renewal of the buildings.To this end a model based on fuzzy logic was prepared. To construct and to test this model many detailed technical-static expert reports were available all related to a stock of residential buildings in Budapest. Based on this report a database was created. With the help of this database a model was prepared, calculating a so-called status characteristic value between 0 and 1 on the basis of the structures and status of the buildings. For this calculation a fuzzy singleton signature model was prepared. Based on this a hierarchy can be set up related to the stock of buildings, which is suitable for supporting the decision making on intervention. The model was examined by using the created database. Membership values characterising the status of the load-bearing structures-were defined on the basis of the deterioration of the structures. In this chapter a new method for the determination of the membership values is described, which in addition to the deteriorations of the structures takes into account other parameters of the structures, and the impact exerted on the quality of the structure, too. The method is suitable for the determination of the membership values of all primary and secondary structures. As an example the membership values of the foundation structures of the buildings in the database were defined and the results were analysed. The method was elaborated by the use of "real fuzzy values" (R-fuzzy sets), an extension of the concept of classic fuzzy sets, the former being suitable for simultaneously taking into account various aspects. © Springer International Publishing Switzerland 2014.

Open Access: Yes

DOI: 10.1007/978-3-319-03206-1_4

Using Fuzzy Cognitive Maps approach to identify integrated waste management system characteristics

F. Hatwágner A. Buruzs L. T. Koczy

Publication Name: 5th IEEE International Conference on Cognitive Infocommunications Coginfocom 2014 Proceedings

Publication Date: 2014-01-23

Volume: Unknown

Issue: Unknown

Page Range: 141-147

Description:

This paper outline how Fuzzy Cognitive Maps (FCM) can be applied as a tool in integrated waste management systems. FCM is a soft systems methodology for exploiting and analyzing human perceptions of a given system. During the research, the driving forces and impacts in the changes of waste management systems have been analyzed. Several types of FCM are known, and the authors' intention was to apply the FCM type III to describe the causality relations among the factors of the integrated waste management systems (IWMS).

Open Access: Yes

DOI: 10.1109/CogInfoCom.2014.7020435

Improving the accuracy of a fuzzy-based single-stroke character recognizer by antecedent weighting

Alex Tormási L. T. Koczy

Publication Name: Studies in Fuzziness and Soft Computing

Publication Date: 2014-01-01

Volume: 317

Issue: Unknown

Page Range: 165-179

Description:

In this chapter we present an improved version of the fuzzy based single-stroke character recognizer introduced in previous works. The modified recognition method is able to reach higher accuracy in the character recognition without any significant effect on the computational complexity of the algorithm. Different fuzzy rule and antecedent weighting techniques were successfully used to improve the efficiency of fuzzy systems especially in classification problems. The altered recognizer reached 99.49 % average recognition rate with 26 different single-stroke symbols (based on Palm’s Graffiti alphabet) without learning userspecific parameters or modifying the rule-base. The new algorithm has the same computational complexity as the original system does.

Open Access: Yes

DOI: 10.1007/978-3-319-06323-2_11

Complex Building’s Decision Support Method Based on Fuzzy Signatures †

Ádám Bukovics Ferenc Lilik L. T. Koczy

Publication Name: Buildings

Publication Date: 2024-06-01

Volume: 14

Issue: 6

Page Range: Unknown

Description:

In the inner areas of large cities, many residential buildings built at the turn of the 19th and 20th centuries remain standing. The maintenance and renovation of these buildings have emerged as critical priorities over recent decades. E.g., in Budapest during the socialist era, the majority of these buildings were not renovated, and maintenance was largely neglected. In the subsequent 10–15 years following the end of socialism, financial resources for renovations were scarce due to the extensive transfer of properties from state to private ownership. It is only in the last decade or so that renovations have begun to be systematically addressed. Consequently, a significant portion of the building stock is still pending renovation. Given the current economic conditions, sustainable maintenance and necessary conversion are of paramount importance. Unfortunately, few standardized condition assessment methods are implemented in industrial practice, and the literature on this topic is limited. To address these challenges, we have developed an algorithm and model for condition assessment and decision support, which we refer to as the Complex Building’s Decision Support System based on Fuzzy Signatures (CBDF system). Our model employs a fuzzy signature-based approach to account for uncertainties, errors, and potentially missing data that may arise during the assessment process. The primary aim of this model is to equip professionals involved in building condition assessment with a tool that enables them to make consistent and objective decisions while minimizing errors. This paper provides a brief overview of the CBDF system and presents test results from the assessment of a selected structural component of a building, demonstrating the system’s functionality.

Open Access: Yes

DOI: 10.3390/buildings14061630

A stochastic model for analyzing the interpretability-accuracy trade-off in interpretable fuzzy systems using nested Hyperball structures

Krisztián Balázs L. T. Koczy

Publication Name: 8th Conference of the European Society for Fuzzy Logic and Technology Eusflat 2013 Advances in Intelligent Systems Research

Publication Date: 2013-12-01

Volume: 32

Issue: Unknown

Page Range: 72-79

Description:

Our recent work proposed a new meaning preservation approach together with a parameterizable nested hyperball structured search space for interpretable fuzzy systems in order to solve a problem of inconsistency observed in conventional interpretable fuzzy knowledge bases and simultaneously to address the adjustment of the trade-off between interpretability and accuracy. Based on intuitive reasonings and simulation results a conjecture was formulated about favorable trade-off adjustment properties of the proposed method. The aim of the present paper is to construct a mathematical model, in which the conjectured properties can be analyzed and formally verified. Some computational considerations about the interpretation of the resulting knowledge bases are also made. © 2013. The authors -Published by Atlantis Press.

Open Access: Yes

DOI: DOI not available

Non-parametric and parametric t-norms applied in fuzzy rule extraction

László Gál Rita Lovassy L. T. Koczy

Publication Name: Iccc 2013 IEEE 9th International Conference on Computational Cybernetics Proceedings

Publication Date: 2013-11-07

Volume: Unknown

Issue: Unknown

Page Range: 299-302

Description:

In this paper we propose non-parametric t-norms such as algebraic, trigonometric and Hamacher product, furthermore parametric Hamacher t-norm in Mamdani type inference systems. Various models with trapezoidal shaped fuzzy membership function are applied in order to improve the efficiency of bacterial memetic algorithm in automatic fuzzy rule identification. © 2013 IEEE.

Open Access: Yes

DOI: 10.1109/ICCCyb.2013.6617607

Solution of a fuzzy resource allocation problem by various evolutionary approaches

P. Földesi Zsolt Dányádi L. T. Koczy

Publication Name: Proceedings of the 2013 Joint Ifsa World Congress and NAFIPS Annual Meeting Ifsa NAFIPS 2013

Publication Date: 2013-10-31

Volume: Unknown

Issue: Unknown

Page Range: 807-812

Description:

In this paper we present a fuzzy resource allocation and assignment problem and propose two types of biologically inspired optimization methods to solve it. The resources in question are used for the maintenance of a network of nodes, each with its specific maintenance demands over time. Our goal is to assign sufficient capacities to storage locations and transport the appropriate amount of resources to the nodes at specific times during the simulation, so that the total cost of storage, transportation and malfunction is kept to a minimum. We use fuzzy numbers to describe the parameters of all the scenarios a solution has to fit, such as the maintenance demands of each node, the additional expenditure that malfunctions bring, and also the varying cost of transportation between nodes and storage locations. The optimization methods we used were the bacterial evolutionary algorithm and the particle swarm algorithm, both with a plain and a memetic variant complemented with gradient-based local search. All of them had a version where they only worked with crisp values, and one with fuzzy solutions. We tested the effectiveness of these four approaches on four examples with varying network sizes and durations. © 2013 IEEE.

Open Access: Yes

DOI: 10.1109/IFSA-NAFIPS.2013.6608504

Meta-heuristic optimization of a fuzzy character recognizer

Alex Tormási L. T. Koczy

Publication Name: Studies in Fuzziness and Soft Computing

Publication Date: 2015-01-01

Volume: 326

Issue: Unknown

Page Range: 227-244

Description:

Meta-heuristic algorithms are well researched and widely used in optimization problems. There are several meta-heuristic optimization algorithms with various concepts and each has its own advantages and disadvantages. Still it is difficult to decide which method would fit the best to a given problem. In this study the optimization of a fuzzy rule-base from a classifier, more specifically fuzzy character recognizer is used as the reference problem and the aim of the research was to investigate the behavior of selected meta-heuristic optimization techniques in order to develop a multi meta-heuristic algorithm.

Open Access: Yes

DOI: 10.1007/978-3-319-19683-1_13

Comparing the efficiency of a fuzzy single-stroke character recognizer with various parameter values

Alex Tormási L. T. Koczy

Publication Name: Communications in Computer and Information Science

Publication Date: 2012-11-02

Volume: 297 CCIS

Issue: PART 1

Page Range: 260-269

Description:

In this paper the results of a study on the accuracy of a fuzzy logic-based single-stroke character recognizer are presented by refining various parameter values, such as resolution of the fuzzy grid and the minimum distance between sampled points. The symbol set is a modified version of Palm's Graffiti single-stroke alphabet and it contains 26 different symbols. Each symbol is represented by a single fuzzy rule. The rule base was determined by a subset of the collected samples. 99.4% recognition rate has been achieved with the initial rule base, without training. With the revised parameter values the accuracy is close or even slightly beyond the results of other academic or commercial systems. © 2012 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-642-31709-5_27

Context recognition in mobile robots cooperation using fuzzy signature

R. C. Pozna Á Ballagi L. T. Koczy

Publication Name: International Conference on Theoretical and Mathematical Foundations of Computer Science 2010 Tmfcs 2010

Publication Date: 2010-12-01

Volume: Unknown

Issue: Unknown

Page Range: 110-115

Description:

Robots cooperation means also to define the commune task. In order to understand their cooperation the robots must have complete knowledge about all possible states of the work or to understand the context by extract useful information from observation. Present paper focus on the second possibility. We propose a strategy of information extraction and context understanding based on an original data structure, the fuzzy signature and on a priori knowledge, the robot codebook. The paper starts by presenting the concept of the fuzzy signature and exemplify the idea of cooperation by context understanding.

Open Access: Yes

DOI: DOI not available

A fuzzy bacterial evolutionary solution for crisp three-dimensional bin packing problems

P. Földesi Dányádi Zsolt L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2012-10-23

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

This paper presents an evolutionary quasi-solution for a problem commonly occurring in practical logistics, the three-dimensional version of the bin packing problem. The algorithm presented here is a variation of the bacterial evolutionary approach, and utilizes fuzzy logic in the fitness calculation. The goal is to give a useful alternative method to the basic problem, and to demonstrate that the addition of fuzzy logic elements to the fitness function increases the speed of the evolutionary process. The paper first describes the specific problem, then moves on to the details of every key part of the algorithm. Finally, the results from a number of test runs are used to show the general efficiency, and the contrast between the crisp and fuzzy fitness functions. It is clearly shown that the application of fuzzy approach in the fitness function can improve the speed of convergence, so the fuzzy logic can be helpful even in solving crisp problems. © 2012 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZ-IEEE.2012.6251262

Determining an optimal subdivision of gene transfer partitions

J. Botzheim P. Földesi Mark Farkas L. T. Koczy

Publication Name: Proceedings of the 9th Wseas International Conference on Applied Computer and Applied Computational Science Acacos 10

Publication Date: 2010-12-01

Volume: Unknown

Issue: Unknown

Page Range: 202-207

Description:

Bacterial memetic algorithms are widely used on discrete combinatorial problems, which are essential in the field of logistics and forwarding, such as the well known Traveling Salesman Problem. The original Bacterial Evolutionary Algorithm proposed by Nawa and Furuhashi [5] has a predefined set of operators such as bacterial mutation and gene transfer also known as infection. The traditional bacterial infection operator is proven to be far from optimal. The authors suggest an alternative gene transfer operator that is applied on the metric Traveling Salesman Problem [9]. This alternative infection algorithm has superior rate of convergence while reducing the risk of getting stuck in a local optima.

Open Access: Yes

DOI: DOI not available

On the existence and uniqueness of fixed points of fuzzy set valued sigmoid fuzzy cognitive maps

István Harmati L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2018-10-12

Volume: 2018-July

Issue: Unknown

Page Range: Unknown

Description:

Fuzzy cognitive maps are decision support tools, where the complex structure is modelled by a weighted, directed graph. The nodes represent specific characteristics of the modelled system, weighted and directed edges correspond to the direction and the strength of the relationship between the factors. The system state is identified by the values of the nodes which are computed by iteration. This process may lead to a fixed point, a limit cycle or produces chaotic behaviour. The type of behaviour depends on the weights, on the topology of the graph and on the function applied for the iteration. From the practical viewpoint, it is critical to know whether the iteration converges to a fixed point or not. In this article, we discuss this problem for the case when the weights or the values of the nodes are fuzzy numbers. This scenario may occur when linguistic variables, modelled by fuzzy numbers, describe the connections.

Open Access: Yes

DOI: 10.1109/FUZZ-IEEE.2018.8491447

Global stability of fuzzy cognitive maps

F. Hatwágner István Harmati L. T. Koczy

Publication Name: Neural Computing and Applications

Publication Date: 2023-04-01

Volume: 35

Issue: 10

Page Range: 7283-7295

Description:

Complex systems can be effectively modelled by fuzzy cognitive maps. Fuzzy cognitive maps (FCMs) are network-based models, where the connections in the network represent causal relations. The conclusion about the system is based on the limit of the iteratively applied updating process. This iteration may or may not reach an equilibrium state (fixed point). Moreover, if the model is globally asymptotically stable, then this fixed point is unique and the iteration converges to this point from every initial state. There are some FCM models, where global stability is the required property, but in many FCM applications, the preferred scenario is not global stability, but multiple fixed points. Global stability bounds are useful in both cases: they may give a hint about which parameter set should be preferred or avoided. In this article, we present novel conditions for the global asymptotical stability of FCMs, i.e. conditions under which the iteration leads to the same point from every initial vector. Furthermore, we show that the results presented here outperform the results known from the current literature.

Open Access: Yes

DOI: 10.1007/s00521-021-06742-9

Eugenic bacterial memetic algorithm for fuzzy road transport traveling salesman problem

J. Botzheim P. Földesi L. T. Koczy

Publication Name: International Journal of Innovative Computing Information and Control

Publication Date: 2011-05-01

Volume: 7

Issue: 5 B

Page Range: 2775-2798

Description:

The aim of the Traveling Salesman Problem (TSP) is to find the cheapest way of visiting all elements in a given set of cities (nodes) exactly once and returning to the starting point. In solutions presented in the literature costs of travel between nodes are based on Euclidean distances, the problem is symmetric and the costs are constant and crisp values. Practical application in road transportation and supply chains are often uncertain or fuzzy. The risk attitude depends on the features of the given operation. The model presented in this paper handles the fuzzy, time dependent nature of the TSP and also gives a solution for the asymmetric loss aversion by embedding the risk attitude into the fitness function of the eugenic bacterial memetic algorithm. Computational results are presented for different cases. The classical TSP is investigated along with a modified instance where some costs between the cities are described with fuzzy numbers. Two different techniques are proposed to evaluate the uncertainties in the fuzzy cost values. The time dependent version of the fuzzy TSP is also investigated and simulation experiences are presented. © 2011.

Open Access: Yes

DOI: DOI not available

Improved Method for Predicting the Performance of the Physical Links in Telecommunications Access Networks

Ferenc Lilik L. T. Koczy Szilvia Nagy

Publication Name: Complexity

Publication Date: 2018-01-01

Volume: 2018

Issue: Unknown

Page Range: Unknown

Description:

A novel approach is presented which is able to predict the available maximal data transfer rate of SHDSL connections from measured frequency dependent electrical parameters of wire pairs. Predictions are made by a fuzzy inference system. The basis of the operable and tested method will be introduced, then an improved version is shown, in which the problems derived from sampling of continuous functions of electrical parameters are eliminated by wavelet transformation. Also possibilities for simplification of the problem and a way of reducing the dimensions of the applied rule bases are presented. As the set of the measured data leads to sparse rule bases, handling of sparseness is unavoidable. Two different ways - fuzzy interpolation and various membership functions - will be introduced. The presented methods were tested by measurements in real telecommunications access networks.

Open Access: Yes

DOI: 10.1155/2018/3685927

Fuzzy-based multi-stroke character recognizer

Alex Tormási L. T. Koczy

Publication Name: 2013 Federated Conference on Computer Science and Information Systems Fedcsis 2013

Publication Date: 2013-12-01

Volume: Unknown

Issue: Unknown

Page Range: 671-674

Description:

In this paper an extension for multi-stroke character recognition of FUzzy BAsed handwritten character Recognition (FUBAR) algorithm will be presented. First the basic concept of a single-stroke version will be overviewed; in the second part of the paper the new version of the algorithm with multi-stroke symbol support will be introduced, which deploy the same algorithm overviewed in the first part and use flat and hierarchical rule bases. © 2013 Polish Information Processing Society.

Open Access: Yes

DOI: DOI not available

On the sensitivity of weighted general mean based type-2 fuzzy signatures

István Harmati L. T. Koczy

Publication Name: Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

Publication Date: 2016-01-01

Volume: 9692

Issue: Unknown

Page Range: 206-218

Description:

Fuzzy signatures offer a possible way of describing, modeling and analysing of complex systems, when the exact mathematical model is not known or too difficult to handle. In these cases the input values have uncertainties, due to lack of knowledge or human activities. These uncertainties have influence on the final decision about the system. The uncertainties are taken into consideration as fuzzy sets, for example representing the uncertainty of a linguistic variable. In this paper we discuss the input sensitivity of type-2 weighted general mean aggregation operator and fuzzy signatures which are equipped with general means as aggregation operators.

Open Access: Yes

DOI: 10.1007/978-3-319-39378-0_19

Fuzzy signature based description of complex overtaking and engagement conflicts in railway traffic control

Gábor Rózsa Á Ballagi L. T. Koczy

Publication Name: IEEE AFRICON Conference

Publication Date: 2015-11-18

Volume: 2015-November

Issue: Unknown

Page Range: Unknown

Description:

The railway traffic system and its respective subsystems, especially station and timetable management are extremely large and complex systems comprising a multitude of complex structured data. The theoretical and pre-planned traffic control is calculating with idealized traffic situations, but the real life scenes often suffer from conflicts and deviations. The complex traffic conflict states include uncertain conditions and vagueness of information. Classical methods cannot work properly under these uncertain conditions. In this paper we propose a new approach to describe these complex conflict situations using fuzzy signatures for recognizing and describing traffic conflicts in a hierarchically structured manner.

Open Access: Yes

DOI: 10.1109/AFRCON.2015.7331929

Parameter dependence of fuzzy cognitive maps' behaviour

F. Hatwágner A. Torma L. T. Koczy

Publication Name: 2015 10th Asian Control Conference Emerging Control Techniques for A Sustainable World Ascc 2015

Publication Date: 2015-09-08

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Stakeholder Relationship Management Systems (SRMS) are conventionally analyzed by a static way, which hides the interconnections of the system. Authors investigated a novel approach to make the evaluation of the interconnections of the SRMS and their behavior achievable. The Fuzzy Cognitive Maps (FCM) is a proper tool to investigate the properties of SRMS. The simulation of SRMS with FCM supports the business management process and different project support activities. If the factors of SRMS themselves, the initial states of them and causality relations among them are already determined, a simulation can be easily carried out. In some specific situations the results of the simulation is hard to use in practice, however. If the differences between factor states are very small, the order (importance) of factors cannot be defined. In such cases the modification of the threshold function's parameter can help to better separate final factor states. This paper deals with the investigation of this approach.

Open Access: Yes

DOI: 10.1109/ASCC.2015.7244823

Function approximation performance of Fuzzy Neural Networks based on frequently used fuzzy operations and a pair of new trigonometric norms

László Gál Rita Lovassy L. T. Koczy

Publication Name: 2010 IEEE World Congress on Computational Intelligence Wcci 2010

Publication Date: 2010-11-25

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

A new triangular t-norm and t-conorm are presented. The new fuzzy operations combined with the standard negation are applied in a practical problem, namely, they are proposed as suitable triangular norms for defining a fuzzy flip-flop based neuron. Other fuzzy J-K and D flip-flop based neurons are constructed by using algebraic, Lukasiewicz, Yager, Dombi and Hamacher connectives. The function approximation performance of a Fuzzy Neural Networks (FNN) built up from various fuzzy neurons are evaluated using six increasingly more complicated problems: various sine waves, battery cell charging characteristics, two dimensional trigonometric functions and a six dimensional benchmark problem. It is shown that the new norms lead to FNNs with better approximation properties in some cases than all the previous ones. © 2010 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2010.5584252

Which players will leave their community? Predicting guild abandonments in world of warcraft game data

Gergely Posfai Gabor Magyar L. T. Koczy

Publication Name: Ifsa Scis 2017 Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems

Publication Date: 2017-08-30

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

World of Warcraft (WoW) is one of the most popular massively multiplayer online role-playing games (MMORPGs) having more than 10 million subscribers over the world. In order to engage and retain users understanding and predicting their behavior can be very useful for game developers. An important component of WoW are so-called guilds, which are social communities whose members can act together efficiently to accomplish more difficult goals and also provide a social atmosphere in which the game might be more entertaining. In this paper, we build predictive models to forecast which of the players will leave their guild in the close future. Our best model uses fuzzy c-means clustering to capture groups of similar guilds, that serve as the basis of an ensemble model, which computes predictions for each cluster separately and combines individual predictions into one final prediction using the memberships of the fuzzy clusters. Empirical analysis on WoW game data shows that our methods convincingly outperform the only existing method in the literature. To ensure transparency and reproducibility we publish the source codes of the research and also provide a Docker image, which makes it possible for anyone who has Docker installed to reproduce all of our results with a single command.

Open Access: Yes

DOI: 10.1109/IFSA-SCIS.2017.8023234

An effective Discrete Bacterial Memetic Evolutionary Algorithm for the Traveling Salesman Problem

P. Földesi Boldizsar Tuu-Szabo L. T. Koczy

Publication Name: International Journal of Intelligent Systems

Publication Date: 2017-08-01

Volume: 32

Issue: 8

Page Range: 862-876

Description:

In recent years, a large number of evolutionary and other population-based heuristics were proposed in the literature. In 2009, we suggested to combine the very efficient bacterial evolutionary algorithm with local search as a new Discrete Bacterial Memetic Evolutionary Algorithm (DBMEA) (Farkas et al., In: Towards intelligent engineering & information technology, Studies in Computational Intelligence, Vol 243. Berlin, Germany: Springer-Verlag; 2009. pp 607–625). The method was tested on one of Traveling Salesman Problem (TSP) benchmark problems, and a difference was found between the real optimum calculated by the new and the published result because the Concorde and the Lin–Kernighan algorithm use an approximation substituting distances of points by the closest integer values. We modified the Concorde algorithm using real cost values to compare with our results. In this paper, we systematically investigate TSPLIB benchmark problems and other VLSI benchmark problems (http://www.math.uwaterloo.ca/tsp/vlsi/index.html) and compare the following values: optima found by the DBMEA heuristic and by the modified Concorde algorithm with real cost values, run times of DBMEA, modified Concorde, and Lin–Kernighan heuristic. In this paper, for the evaluation of metaheuristic techniques, we suggest the usage of predictability of the successful run in addition to the accuracy of the result and the computational cost as third property. We will show that in the case of DBMEA, the run time is more predictable than in the case of Concorde algorithm, so we suggest the use of DBMEA heuristic as very efficient for the solution of TSP and other nondeterministic polynomial-time hard optimization problems.

Open Access: Yes

DOI: 10.1002/int.21893

A new fuzzy graph and signature based approach to describe fuzzy situational maps

R. C. Pozna Á Ballagi L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2014-09-04

Volume: Unknown

Issue: Unknown

Page Range: 1340-1345

Description:

Computational tasks involving intelligent agents often need to process complex structured information. The way of describing this information greatly influences the performance of the agent. Therefore, a big issue is how the complex data describing that valuable information is not lose while it can also be processed in tractable time. Fuzzy signatures and their multidimensional geometric extension, fuzzy situational maps, are used to describe such complex structured data. These problems are examined in the context of a cooperative mobile robot task and a new method is developed for the simplified describing and processing of the complex inner relations in fuzzy situational maps. This paper mainly deals with the fundamentals of this method.

Open Access: Yes

DOI: 10.1109/FUZZ-IEEE.2014.6891862

Doctoral symposium on recent advances in information technology

Ferenc Lilik Piotr Kulczycki L. T. Koczy Piotr Andrzej Kowalski Dominika Golunska Szymon Lukasik Jaroslaw Arabas Alex Tormási Radko Mesiar Krisztián Balázs Krassimir T. Atanassov Modesto Castrillon-Santana Malgorzata Charytanowicz Thomas Corpetti Nicolas Courty Philippe Fournier-Viger David Gil Bao Gang Hu Carles Noguera I Clofent Milan Petrik Yujiu Yang Slawomir Zadrozny

Publication Name: 2013 Federated Conference on Computer Science and Information Systems Fedcsis 2013

Publication Date: 2013-12-01

Volume: Unknown

Issue: Unknown

Page Range: 637

Description:

No description provided

Open Access: Yes

DOI: DOI not available

Motion control and communication of cooperating intelligent robots by fuzzy signatures

T. D. Gedeon Á Ballagi L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2009-12-10

Volume: Unknown

Issue: Unknown

Page Range: 1073-1078

Description:

This paper presents two examples of usage of fuzzy signatures in the field of mobile robotics. The first shows a complex lateral drift control method base on fuzzy signatures. This method inspects the motion system of the robot as a whole, unlike as simple parts of a complex system. The state space is written down by fuzzy signatures which add up flexibility, adaptability and learning ability to the system. In the second experiment a new communication approach is investigated for intelligent cooperation of autonomous mobile robots. Effective, fast and compact communication is one of the most important cornerstones of a high-end cooperating system. In this paper we propose a fuzzy communication system where the codebooks are built up by fuzzy signatures. We use cooperating autonomous mobile robots to solve some logistic problems. ©2009 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2009.5277207

Historical origin of the fine structure constant: Part III: Pauli with Jung Retro-Cognizes St. Stephen's crowning achievement

P. Várlaki L. T. Koczy I. J. Rudas

Publication Name: Acta Polytechnica Hungarica

Publication Date: 2011-12-01

Volume: 8

Issue: 6

Page Range: 43-78

Description:

In Part II of the paper we discussed the central role of the number-archetype 137 in some great medieval works related to St Stephen's court. On the basis of the hermeneutical interpretation of certain of Pauli's famous dream series, we intend to show his hypothetical "synchronistic (unconscious) recognition" of the dominant representations and meanings of the medieval works discussed in the earlier parts of this paper, which can be related to his isomorphic mythological and "physical" dream patterns. We can also conclude that Pauli, collaborating with Jung, himself confirms in his consistent "dream-messages" the symbolic meaningful relationship and structural isomorphy between the basic quantum-physical model's features (e.g. the fine structure constant) and their hypothetical primordial images appearing even in the actual medieval works.

Open Access: Yes

DOI: DOI not available

Exploring Fuzzy Signatures in Sensor Fusion: A Comparative Study with the Complementary Filter

Á Ballagi Ahmet Mehmet Karadeniz L. T. Koczy

Publication Name: Cinti 2024 IEEE 24th International Symposium on Computational Intelligence and Informatics Proceedings

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: 69-74

Description:

Sensing has become a pivotal element in the development of autonomous systems with the advancement of the technology. These systems operate on a sense-think-act cycle to execute tasks, necessitating the integration of multiple sensors. The challenge of synthesizing meaningful information from diverse data sources escalates with the complexity of the data. This study tackles the issue of sensor data complexity by investigating the potential of Fuzzy Signatures, which are promising in handling complex data due to their hierarchical structures. The main goal is to present a concept for sensor fusion based on Fuzzy Signatures, which may facilitate their use in autonomous system tasks. To demonstrate this concept, accelerometer and gyroscope data are utilized, with results compared to those from a Complementary Filter providing insight into the sensor fusion capabilities of Fuzzy Signatures. The study also underscores the importance of aggregation operators in Fuzzy Signatures, focusing on the Max and WRAO (weighted relevance aggregation operator) aggregation operators. The potential to employ various aggregation operators or to develop new ones for specific applications is highlighted. The findings indicate that Fuzzy Signatures could be an effective solution for sensor fusion challenges, offering prospects for enhancement and broader application in autonomous systems.

Open Access: Yes

DOI: 10.1109/CINTI63048.2024.10830837

Hierarchical fuzzy system construction applying genetic and bacterial programming algorithms with expression tree building restrictions

J. Botzheim Krisztián Balázs L. T. Koczy

Publication Name: 2010 World Automation Congress Wac 2010

Publication Date: 2010-12-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

In this paper various restrictions are proposed in the construction of hierarchical fuzzy rule bases by using Genetic and Bacterial Programming algorithms in order to model black box systems defined by input-output pairs, i.e. to solve supervised machine learning problems. The properties (learning speed, accuracy) of the established systems are observed based on simulation results and they are compared to each other. © 2010 TSI Press.

Open Access: Yes

DOI: DOI not available

Fuzzy communication in collaboration of intelligent agents

Á Ballagi L. T. Koczy

Publication Name: Proceedings of the 9th Wseas International Conference on Applied Computer and Applied Computational Science Acacos 10

Publication Date: 2010-12-01

Volume: Unknown

Issue: Unknown

Page Range: 208-214

Description:

This paper presents some examples for fuzzy communication and intention guessing from the real life to the cooperation of intelligent mobile robots. In a special experimental environment a new communication approach is investigated for intelligent cooperation of autonomous mobile robots. Effective, fast and compact communication is one of the most important cornerstones of a high-end cooperating system. In this paper we propose a fuzzy communication system where the codebooks are built up by fuzzy signatures. We use cooperating autonomous mobile robots to solve some logistic problems.

Open Access: Yes

DOI: DOI not available

Hardware implementation of fuzzy flip-flops based on łukasiewicz norms

Antonio Hernández Zavala László Gál Rita Lovassy Ildar Batyrshin Oscar Camacho Nieto L. T. Koczy

Publication Name: Proceedings of the 9th Wseas International Conference on Applied Computer and Applied Computational Science Acacos 10

Publication Date: 2010-12-01

Volume: Unknown

Issue: Unknown

Page Range: 196-201

Description:

The digital hardware implementation of various fuzzy operations furthermore of fuzzy flip-flops has been the subject of intense study and application. The fuzzy D flip-flop derived from fuzzy J-K one is a single input - single output unit with sigmoid transfer characteristics in some particular cases, proper to use as neuron in a Fuzzy Neural Networks (FNN). In this paper we propose the hardware realization of fuzzy D flip-flops based on Łukasiewicz norms.

Open Access: Yes

DOI: DOI not available

Evaluation of Questionnaires by Combining Fuzzy Signatures, Factor Analysis and Least Squares Method

D. Susniene Marta Szombathelyi Szabolcs Ramhap Ojaras Purvinis L. T. Koczy

Publication Name: Ines 2020 IEEE 24th International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2020-07-01

Volume: Unknown

Issue: Unknown

Page Range: 215-218

Description:

A survey based on a standard questionnaire on employee satisfaction was carried out in Hungary. The questionnaire was developed by international university research consortium. The qualitative data were collected from 1159 respondents. The subjective and therefore inexact answers represented in the Likert scale were mapped into fuzzy membership degrees. The article presents a method that consists of the combination of factor analysis and the least square method, applied for developing the fuzzy signature characterizing the employees' behavioural engagement.

Open Access: Yes

DOI: 10.1109/INES49302.2020.9147125

Solution for fuzzy road transport traveling salesman problem using eugenic bacterial memetic algorithm

J. Botzheim P. Földesi L. T. Koczy

Publication Name: 2009 International Fuzzy Systems Association World Congress and 2009 European Society for Fuzzy Logic and Technology Conference Ifsa Eusflat 2009 Proceedings

Publication Date: 2009-12-01

Volume: Unknown

Issue: Unknown

Page Range: 1667-1672

Description:

The aim of the Traveling Salesman Problem (TSP) is to find the cheapest way of visiting all elements in a given set of cities and returning to the starting point. In solutions presented in the literature costs of travel between nodes (cities) are based on Euclidean distances, the problem is symmetric and the costs are constant. In this paper a novel construction and formulation of the TSP is presented in which the requirements and features of practical application in road transportation and supply chains are taken into consideration. Computational results are presented as well.

Open Access: Yes

DOI: DOI not available

Comparative analysis of various evolutionary and memetic algorithms

J. Botzheim Krisztián Balázs L. T. Koczy

Publication Name: 10th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics Cinti 2009

Publication Date: 2009-12-01

Volume: Unknown

Issue: Unknown

Page Range: 193-205

Description:

Optimization methods known from the literature include gradient techniques and evolutionary algorithms. The main idea of gradient methods is to calculate the gradient of the objective function at the actual point and then to step towards better values according to this value. Evolutionary algorithms imitate a simplified abstract model of evolution observed in nature. Memetic algorithms traditionally combine evolutionary and gradient techniques to exploit the advantages of both methods. Our current research aims to discover the properties, especially the efficiency (i.e. the speed of convergence) of particular evolutionary and memetic algorithms. For this purpose the techniques are compared by applying them on several numerical optimization benchmark functions and on fuzzy rule base identification.

Open Access: Yes

DOI: DOI not available

Reduced model investigations supported by fuzzy cognitive map to foster circular economy

F. Hatwágner A. Buruzs L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2019-01-01

Volume: 796

Issue: Unknown

Page Range: 191-202

Description:

The aim of the present paper is to develop an integrated method that provide assistance to decision makers during system planning, design, operation and evaluation. In order to support the realization of Circular Economy (CE) it is essential to evaluate local needs and conditions that help to select the most appropriate system-components and resources needed. Each of these activities requires careful planning, however, the model of CE offers a comprehensive interdisciplinary framework. The aim of this research was to develop and to introduce a practical methodology for evaluation of local and regional opportunities to promote CE.

Open Access: Yes

DOI: 10.1007/978-3-030-00485-9_22

Quasi optimization of fuzzy neural networks

László Gál Rita Lovassy L. T. Koczy

Publication Name: 10th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics Cinti 2009

Publication Date: 2009-12-01

Volume: Unknown

Issue: Unknown

Page Range: 303-314

Description:

The fuzzy flip-flop based multilayer perceptron, named Fuzzy Neural Network, FNN is proposed for function approximation. In recent years much effort has been made for the development of a special kind of bacterial memetic algorithm for optimization and training of the fuzzy neural network parameters. In this approach the FNN parameters have been encoded in a chromosome and participate in the bacterial mutation cycle. The quasi optimized FNN's performance based on various fuzzy flip-flop types has been examined with a series of multidimensional input functions.

Open Access: Yes

DOI: DOI not available

Optimizing fuzzy flip-flop based neural networks by bacterial memetic algorithm

László Gál Rita Lovassy L. T. Koczy

Publication Name: 2009 International Fuzzy Systems Association World Congress and 2009 European Society for Fuzzy Logic and Technology Conference Ifsa Eusflat 2009 Proceedings

Publication Date: 2009-12-01

Volume: Unknown

Issue: Unknown

Page Range: 1508-1513

Description:

In our previous work we proposed a Multilayer Perceptron Neural Networks (MLP NN) consisting of fuzzy flipflops (F³) based on various operations. We showed that such kind of fuzzy-neural network had good learning properties. In this paper we propose an evolutionary approach for optimizing fuzzy flip-flop networks (FNN). Various popular fuzzy operation and three different fuzzy flip-flop types will be compared from the point of view of the respective fuzzy-neural networks' approximation capability.

Open Access: Yes

DOI: DOI not available

Approximation of a modified traveling salesman problem using bacterial memetic algorithms

J. Botzheim P. Földesi Mark Farkas L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2009-12-01

Volume: 243

Issue: Unknown

Page Range: 607-625

Description:

The goal of this paper is to develop an algorithm that is capable to handle a slightly modified version of the minimal Traveling Salesman Problem in an efficient and robust way and produces high-quality solutions within a reasonable amount of time. The requirements of practical logistical applications, such as road transportation and supply chains, are also taken into consideration in this novel approach of the TSP. This well-known combinatorial optimization task is solved by a bacterial memetic algorithm, which is an evolutionary algorithm inspired by bacterial transduction. A new method is also proposed to deal with the time dependency in the cost matrix. The efficiency of the implementation, including time and space constraints, is investigated on a real life problem. © 2009 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-642-03737-5_44

Intelligent Fuzzy Traffic Signal Control System for Complex Intersections Using Fuzzy Rule Base Reduction

Tamrat Delessa Chala L. T. Koczy

Publication Name: Symmetry

Publication Date: 2024-09-01

Volume: 16

Issue: 9

Page Range: Unknown

Description:

In this study, the concept of symmetry is employed to implement an intelligent fuzzy traffic signal control system for complex intersections. This approach suggests that the implementation of reduced fuzzy rules through the reduction method, without compromising the performance of the original fuzzy rule base, constitutes a symmetrical approach. In recent decades, urban and city traffic congestion has become a significant issue because of the time lost as a result of heavy traffic, which negatively affects economic productivity and efficiency and leads to energy loss, and also because of the heavy environmental pollution effect. In addition, traffic congestion prevents an immediate response by the ambulance, police, and fire brigades to urgent events. To mitigate these problems, a three-stage intelligent and flexible fuzzy traffic control system for complex intersections, using a novel hybrid reduction approach was proposed. The three-stage fuzzy traffic control system performs four primary functions. The first stage prioritizes emergency car(s) and identifies the degree of urgency of the traffic conditions in the red-light phase. The second stage guarantees a fair distribution of green-light durations even for periods of extremely unbalanced traffic with long vehicle queues in certain directions and, especially, when heavy traffic is loaded for an extended period in one direction and the short vehicle queues in the conflicting directions require passing in a reasonable time. The third stage adjusts the green-light time to the traffic conditions, to the appearance of one or more emergency car(s), and to the overall waiting times of the other vehicles by using a fuzzy inference engine. The original complete fuzzy rule base set up by listing all possible input combinations was reduced using a novel hybrid reduction algorithm for fuzzy rule bases, which resulted in a significant reduction of the original base, namely, by 72.1%. The proposed novel approach, including the model and the hybrid reduction algorithm, were implemented and simulated using Python 3.9 and SUMO (version 1.14.1). Subsequently, the obtained fuzzy rule system was compared in terms of running time and efficiency with a traffic control system using the original fuzzy rules. The results showed that the reduced fuzzy rule base had better results in terms of the average waiting time, calculated fuel consumption, and CO2 emission. Furthermore, the fuzzy traffic control system with reduced fuzzy rules performed better as it required less execution time and thus lower computational costs. Summarizing the above results, it may be stated that this new approach to intersection traffic light control is a practical solution for managing complex traffic conditions at lower computational costs.

Open Access: Yes

DOI: 10.3390/sym16091177

Optimizing complex building renovation process with fuzzy signature state machines

G. Molnárka L. T. Koczy

Publication Name: Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

Publication Date: 2014-01-01

Volume: 8835

Issue: Unknown

Page Range: 573-580

Description:

In contrary to recently built office and commercial buildings, the service life of the traditional European residential houses was not calculated. Some estimations exist about the life span of different types of building constructions, however, these estimations may not reassure the owners of urban-type residential houses that were built before the second world war. A thorough and professional renovation may extend the service life of buildings by decades, the question is how to prepare the most effective renovation procedure.As a combination of the fuzzy signature structure and the principles of finite-state machine a new formal method is proposed for generating a tool for supporting the renovation planning, concerning the costs and importance of repair. With the support of information obtained from a given pre-war urban-type residential house, the available technical guides and the contractors’ billing database an optimized renovation process of the roof structure is presented as a case study.

Open Access: Yes

DOI: 10.1007/978-3-319-12640-1_69

The improvement of an existing fuzzy logic rule base for the treatment and simulation of conflicts in the dispositional tasks of a railway traffic control center

Tibor Héray Mark Farkas L. T. Koczy

Publication Name: Proceedings 2009 3rd International Workshop on Soft Computing Applications Sofa 2009

Publication Date: 2009-11-25

Volume: Unknown

Issue: Unknown

Page Range: 203-207

Description:

The paper considers a railway timetable related problem in a simplified form, generated by the delay of one or several incoming trains at a given station. These incoming train delays are either automatically generated or manually entered. Usually there are connecting trains in the timetable, especially in up to date periodic timetables and thus incoming delays might indicate the necessity of introducing a delay with connecting outgoing trains. A hierarchical fuzzy rule base is applied in order to determine the optimal outgoing delay, taking also usual restrictions into consideration. The delays of the incoming trains are modeled by independent exponential distributions and a software simulation is built around the existing rule base. The behavior of the hierarchical fuzzy rule base and the pertinence of the outgoing delay is a subject of further investigation. The delays are also updated periodically that makes the recalculation of outgoing delays necessary from time to time. ¹ © 2009 IEEE.

Open Access: Yes

DOI: 10.1109/SOFA.2009.5254850

An Efficient Tour Construction Heuristic for Generating the Candidate Set of the Traveling Salesman Problem with Large Sizes

P. Földesi Boldizsar Tuu-Szabo L. T. Koczy

Publication Name: Mathematics

Publication Date: 2024-10-01

Volume: 12

Issue: 19

Page Range: Unknown

Description:

In this paper, we address the challenge of creating candidate sets for large-scale Traveling Salesman Problem (TSP) instances, where choosing a subset of edges is crucial for efficiency. Traditional methods for improving tours, such as local searches and heuristics, depend greatly on the quality of these candidate sets but often struggle in large-scale situations due to insufficient edge coverage or high time complexity. We present a new heuristic based on fuzzy clustering, designed to produce high-quality candidate sets with nearly linear time complexity. Thoroughly tested on benchmark instances, including VLSI and Euclidean types with up to 316,000 nodes, our method consistently outperforms traditional and current leading techniques for large TSPs. Our heuristic’s tours encompass nearly all edges of optimal or best-known solutions, and its candidate sets are significantly smaller than those produced with the POPMUSIC heuristic. This results in faster execution of subsequent improvement methods, such as Helsgaun’s Lin–Kernighan heuristic and evolutionary algorithms. This substantial enhancement in computation time and solution quality establishes our method as a promising approach for effectively solving large-scale TSP instances.

Open Access: Yes

DOI: 10.3390/math12192960

Decision-Making Based on Fuzzy Linguistic Signatures

Nour Ammar L. T. Koczy

Publication Name: Ciees 2023 IEEE International Conference on Communications Information Electronic and Energy Systems

Publication Date: 2023-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Decision-making is a key process for human beings, and it is becoming more complicated in the case of uncertainty. Thus, it may be a more realistic approach to use linguistic values instead of numerical values. In the literature, there have been numerous applications for fuzzy signatures for modelling decision-making problems with uncertainty. However, there are application cases where the parameters are not measurable, and there is no way to assign precise membership values and functions to the variables. The main goal of this paper is to propose a way to make a decision about traffic related questions, using a new model for fuzzy linguistic signatures with linguistic aggregation operations in this case. Telemetric data collected by the Hungarian e-toll declaration provider are utilized for the purpose of the example. The results demonstrate the efficiency and time-saving advantages of employing fuzzy linguistic signatures over to numerical methods for decision-making.

Open Access: Yes

DOI: 10.1109/CIEES58940.2023.10378751

Transfer Learning-Based Steering Angle Prediction and Control with Fuzzy Signatures-Enhanced Fuzzy Systems for Autonomous Vehicles

Á Ballagi Ahmet Mehmet Karadeniz L. T. Koczy

Publication Name: Symmetry

Publication Date: 2024-09-01

Volume: 16

Issue: 9

Page Range: Unknown

Description:

This research introduces an innovative approach for End-to-End steering angle prediction and its control in electric power steering (EPS) systems. The methodology integrates transfer learning-based computer vision techniques for prediction and control with fuzzy signatures-enhanced fuzzy systems. Fuzzy signatures are unique multidimensional data structures that represent data symbolically. This enhancement enables the fuzzy systems to effectively manage the inherent imprecision and uncertainty in various driving scenarios. The ultimate goal of this work is to assess the efficiency and performance of this combined approach by highlighting the pivotal role of steering angle prediction and control in the field of autonomous driving systems. Specifically, within EPS systems, the control of the motor directly influences the vehicle’s path and maneuverability. A significant breakthrough of this study is the successful application of transfer learning-based computer vision techniques to extract respective visual data without the need for large datasets. This represents an advancement in reducing the extensive data collection and computational load typically required. The findings of this research reveal the potential of this approach within EPS systems, with an MSE score of 0.0386 against 0.0476, by outperforming the existing NVIDIA model. This result provides a 22.63% better Mean Squared Error (MSE) score than NVIDIA’s model. The proposed model also showed better performance compared with all other three references found in the literature. Furthermore, we identify potential areas for refinement, such as decreasing model loss and simplifying the complex decision model of fuzzy systems, which can represent the symmetry and asymmetry of human decision-making systems. This study, therefore, contributes significantly to the ongoing evolution of autonomous driving systems.

Open Access: Yes

DOI: 10.3390/sym16091180

Analyzing the Performance of TSP Solver Methods

P. Földesi Boldizsar Tuu-Szabo L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2022-01-01

Volume: 955

Issue: Unknown

Page Range: 65-71

Description:

In this paper we analyze the efficiency of three TSP solver methods: the best-performing exact Concorde algorithm, the state-of-the-art inexact Helsgaun’s Lin–Kernighan heuristic and our Discrete Bacterial Memetic Evolutionary Algorithm (DBMEA). In our analysis the run time predictability was also taken into account, not only the tour quality and the run time properties. Three models (polynomial, exponential, square-root exponential) were fitted to the mean run times of VLSI (Very-large-scale integration) instances up to 20,000 nodes. The DBMEA produces the highest (close to 1) R²-values for each model. The Concorde algorithm shows very low run time predictability.

Open Access: Yes

DOI: 10.1007/978-3-030-88817-6_8

Algebraic structure of fuzzy signatures

María Eugenia Cornejo L. T. Koczy Jesús Medina-Moreno

Publication Name: Fuzzy Sets and Systems

Publication Date: 2021-08-15

Volume: 418

Issue: Unknown

Page Range: 25-50

Description:

Fuzzy signatures have been used for various applications, including medical diagnosis, communication of robots based on intention guessing, and residential building evaluation. However, there exist many questions about this research topic which have not been addressed in the literature. One of the most important aims is to formally define a family of fuzzy signatures from which an algebraic structure can be obtained allowing to make computations among fuzzy signatures. This paper studies this family and defines suitable meet and join operators satisfying the properties of a lattice as an algebraic structure. A partial ordering relation, the least and greatest elements are also defined on the family of fuzzy signatures. As a consequence, fuzzy signatures can be used as truth values of fuzzy sets, which provides a great level of representativity, completely different from the interval-valued and type-2 fuzzy sets, among others.

Open Access: Yes

DOI: 10.1016/j.fss.2020.12.020

Robot environment representation based on Quadtree organization of Fuzzy Signatures

Á Ballagi Csaba Hajdu Ahmet Mehmet Karadeniz L. T. Koczy

Publication Name: Saci 2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics Proceedings

Publication Date: 2021-05-19

Volume: Unknown

Issue: Unknown

Page Range: 509-514

Description:

This paper presents a novel approach to mobile robot environment representation to hold information on detected obstacles. The method is inspired by fuzzy signature-based formalism and is based on classical quadtrees as a data indexing structure. Each detected feature point is evaluated by a fuzzy-ruleset defining the presumed significance of each detected object. Feature points and their fuzzy-mapping are indexed in a classical quadtree-based fashion. During the reconstruction of the environment representation, inference is done by the traversal on the constructed tree using accumulated fuzzy-ruleset. Our goal is to use this representation format for further robotic tasks such as obstacle avoidance in a distributed computational environment.

Open Access: Yes

DOI: 10.1109/SACI51354.2021.9465566

A Novel, Three-Stage Intelligent Fuzzy Traffic Signal Control System

Tamrat Delessa Chala L. T. Koczy

Publication Name: Acta Polytechnica Hungarica

Publication Date: 2024-01-01

Volume: 21

Issue: 8

Page Range: 189-209

Description:

Traffic congestion is a serious issue for cities and urban areas, owing to the increasing usage of vehicles. This phenomenon results in several negative consequences, such as high fuel consumption and loss of time. To address this problem, several countries have implemented optimal traffic signal control systems. However, these systems have some drawbacks, such as the need for expensive hardware and maintenance difficulties. Because the sensors are buried under the road surface, the system often cannot account for the full length of the vehicular queue. This, among several issues, inhibits the full potential of the technology’s effectiveness and sustainability. In addition, there is much uncertainty in traffic conditions, which points to the need for a model that includes vagueness in the control system. This study proposes a novel hierarchical structure for a three-stage fuzzy traffic control system. This new system assesses the vehicle queue, identifies heavy traffic, detects emergency cars, and adjusts the duration of traffic lights according to the traffic flow and waiting times of vehicles using fuzzy inference rules. This controller was evaluated and validated using a micro-simulation model of an isolated intersection. The obtained results revealed the increased adaptability and flexibility of the proposed system owing to its potential to differentiate a random number of traffic directions. It is also able to handle emergency vehicles and can decrease waiting times, stalling fewer cars, if there is a high traffic flow in the conflicting direction(s) and is a robust and scalable system with lower computational costs.

Open Access: Yes

DOI: 10.12700/APH.21.8.2024.8.10

Notes on the rescaled algorithm for fuzzy cognitive maps

István Harmati L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2020-01-01

Volume: 819

Issue: Unknown

Page Range: 43-49

Description:

Fuzzy Cognitive Maps are network-like decision support tools, where the final conclusion is determined by an iteration process. Although the final conclusion relies on the assumption that the iteration reaches a fixed point, it is not straightforward that the iteration will converge to anywhere, since it can produce limit cycles or chaotic behaviour also. In this paper, we briefly analyse the behaviour of the so-called rescaled algorithm for fuzzy cognitive maps with respect to the existence and uniqueness of fixed points.

Open Access: Yes

DOI: 10.1007/978-3-030-16024-1_6

Fuzzy Linguistic Signatures and Their Applications

Nour Ammar L. T. Koczy

Publication Name: Ines 2024 28th IEEE International Conference on Intelligent Engineering Systems 2024 Proceedings

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: 27-30

Description:

In the real world, many situations involve dealing with vague and imprecise information, and managing this uncertainty is a big challenge. Numerical-based modeling alone is often insufficient in such cases. As a result, many researchers have implemented fuzzy signatures as a means to overcome this problem. However, there are instances where parameters remain ambiguous, and determining the fuzzy membership degree and membership function as inputs and outputs of such a system is not possible. Therefore, integrating fuzzy signatures with linguistic descriptors provides a more realistic approach to handling uncertain knowledge about the problem. This paper aims to discuss the new fuzzy linguistic signature model, which offers a unique solution by enabling the incorporation of qualitative and quantitative information and explores its potential applications. A software entirely based on linguistic inputs and outputs has been implemented to demonstrate the concept.

Open Access: Yes

DOI: 10.1109/INES63318.2024.10629115

Statistical and fuzzy signature-based analysis of the aggressive attitudes of a forensic population

D. Susniene Daiva Žostautiene Ojaras Purvinis L. T. Koczy

Publication Name: Journal of Infrastructure Policy and Development

Publication Date: 2024-01-01

Volume: 8

Issue: 8

Page Range: Unknown

Description:

Clustering technics, like k-means and its extended version, fuzzy c-means clustering (FCM) are useful tools for identifying typical behaviours based on various attitudes and responses to well-formulated questionnaires, such as among forensic populations. As more or less standard questionnaires for analyzing aggressive attitudes do exist in the literature, the application of these clustering methods seems to be rather straightforward. Especially, fuzzy clustering may lead to new recognitions, as human behaviour and communication are full of uncertainties, which often do not have a probabilistic nature. In this paper, the cluster analysis of a closed forensic (inmate) population will be presented. The goal of this study was by applying fuzzy c-means clustering to facilitate the wider possibilities of analysis of aggressive behaviour which is treated as a heterogeneous construct resulting in two main phenotypes, premeditated and impulsive aggression. Understanding motives of aggression helps reconstruct possible events, sequences of events and scenarios related to a certain crime, and ultimately, to prevent further crimes from happening.

Open Access: Yes

DOI: 10.24294/jipd.v8i8.5727

Machine learning and fuzzy cognitive maps in a hybrid approach toward freeway on-ramp traffic control

F. Hatwágner Mehran Amini L. T. Koczy

Publication Name: Saci 2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics Proceedings

Publication Date: 2023-01-01

Volume: Unknown

Issue: Unknown

Page Range: 587-591

Description:

The infrequent emergence of traffic congestion on freeways can result in the decline of the transportation system over time. Without the implementation of appropriate countermeasures, congestion can escalate, leading to unfavorable impacts on other aspects of the traffic network. As a result, there is a greater need for reliable and optimal traffic control. The goal of this research is to manage the number of vehicles entering the main freeway from the ramp merging area, in order to balance the demand and capacity to satisfy the maximum utilization of the freeway capacity. Despite extensive research into different ramp metering techniques, this study aims to utilize the fuzzy cognitive map as a macroscopic traffic flow model in conjunction with the Q-learning algorithm. This combination prevents freeway congestion and maintains optimal performance by keeping freeway density below a key threshold. The inherent uncertainty of traffic conditions is addressed through the application of reinforcement learning, which is constructed on the principles of the Markov decision process. This approach represents an exploration-exploitation trade-off, as implemented through the Q-learning algorithm. The proposed technique was evaluated for its efficacy in the regulation of freeway ramp metering in both controlled and uncontrolled simulations. The findings demonstrate a significant improvement in the control of the mainstream traffic flow.

Open Access: Yes

DOI: 10.1109/SACI58269.2023.10158585

A transfer learning approach for the classification of liver cancer

Belal Al-Khateeb Fatimah Ihsan Abdulsahib L. T. Koczy Szilvia Nagy

Publication Name: Journal of Intelligent Systems

Publication Date: 2023-01-01

Volume: 32

Issue: 1

Page Range: Unknown

Description:

Problem: The frequency of liver cancer is rising worldwide, and it is a common, deadly condition. For successful treatment and patient survival, early and precise diagnosis is essential. The automated classification of liver cancer using medical imaging data has shown potential outcome when employing machine and deep learning (DL) approaches. To train deep neural networks, it is still quite difficult to obtain a large and diverse dataset, especially in the medical field. Aim: This article classifies liver tumors and identifies whether they are malignant, benign tumor, or normal liver. Methods: This study mainly focuses on computed tomography scans from the Radiology Institute in Baghdad Medical City, Iraq, and provides a novel transfer learning (TL) approach for the categorization of liver cancer using medical images. Our findings show that the TL-based model performs better at classifying data, as in our method, high-level characteristics from liver images are extracted using pre-trained convolutional neural networks compared to conventional techniques and DL models that do not use TL. Results: The proposed method using models of TL technology (VGG-16, ResNet-50, and MobileNetV2) successfully achieves high accuracy, sensitivity, and specificity in identifying liver cancer, making it an important tool for radiologists and other healthcare professionals. The experiment results show that the diagnostic accuracy in the VGG-16 model is up to 99%, ResNet-50 model 100%, and 99% total classification accuracy was attained with the MobileNetV2 model. Conclusion: This proves the improvement of models when working on a small dataset. The use of new layers also showed an improvement in the performance of the classifiers, which accelerated the process.

Open Access: Yes

DOI: 10.1515/jisys-2023-0119

L. T. Koczy

Publications - 315

Robot cooperation without explicit communication by fuzzy signatures and decision trees

Optimization in fuzzy flip-flop neural networks

Robot cooperation by fuzzy signature sets rule base

Exploiting the functional training approach in takagi-sugeno neuro-fuzzy systems

Bacterial memetic algorithm for fuzzy rule base optimization

An hybrid training method for B-spline neural networks

Sensitivity and validity of the fuzzy signature based evaluation of residential building conditions

Modeling integrated sustainable waste management systems using fuzzy cognitive maps and systems of systems concepts

Comparative analysis of interpolative and non-interpolative fuzzy rule based machine learning systems applying various numerical optimization methods

Improving system reliability in optical networks by failure localization using evolutionary optimization

Function approximation capability of a novel fuzzy flip-flop based Neural Network

Performance evaluation of wire pairs in telecommunications networks by fuzzy and evolutionary models

A kantian pattern of knowledge, the observation representation

The application of fuzzy connectives and inverse operations on R-fuzzy descriptors of the static conditions of residential buildings

Multi-threaded Bacterial Iterated Greedy heuristics for the Permutation Flow Shop Problem

Fuzzy Flip-Flop based Neural Networks as a novel implementation possibility of multilayer perceptrons

Design of B-spline neural networks using a bacterial programming approach

Exploiting the functional training approach in B-splines

The possible applications of Fuzzy logic for the treatment of conflicts in the dispositional tasks of railway traffic control centers

Using multiple populations of memetic algorithms for fuzzy rule-base optimization

Historical origin of the fine structure constant subtilis structurae constan unit s1 part i. St. Stephen's crowning achievement

On the issue of learning weights from observations for fuzzy signatures

Comparative investigation of various evolutionary and memetic algorithms

Sensitivity analysis of the weighted generalized mean aggregation operator and its application to fuzzy signatures

A new domain decomposition for B-spline neural networks

Fuzziness and computational intelligence: Dealing with complexity and accuracy

Generalised weighted relevance aggregation operators for hierarchical fuzzy signatures

Fuzzy rule base model identification by bacterial memetic algorithms

Multilayer perceptron implemented by fuzzy flip-flops

Fuzzy search space for correction of cognitive biases in constructing mathematical models

Developing fuzzy cognitive maps for modeling regional waste management systems

A Hybrid Discrete Memetic Algorithm for Solving Flow-Shop Scheduling Problems

Fuzzy flip-flops revisited

Genetic and bacterial memetic programming approaches in hierarchical-interpolative fuzzy system construction

Hybrid Bacterial Iterated Greedy heuristics for the Permutation Flow Shop Problem

Learning generalized weighted relevance aggregation operators using levenberg-marquardt method

Signatures: Definitions, operators and applications to fuzzy modelling

Fuzzy models and interpolation

Mamdani-type inference in fuzzy signature based rule bases

Strategic decision support in waste management systems by state reduction in FCM models

Hierarchical-interpolative fuzzy system construction by Genetic and Bacterial Programming Algorithms

Generalization capability of neural networks based on fuzzy operators

Multi-robot cooperation by fuzzy signature sets

Fuzzy signature based fuzzy communication of mobile robots

Robustness of fuzzy flip-flop based neural networks

Three step bacterial memetic algorithm

Fuzzy communication and motion control by fuzzy signatures in intelligent mobile robots

A comparative study of various evolutionary algorithms used for fuzzy rule-based inference and learning systems

On using fuzzy c-means clustering in the fuzzy signature concept classification of liver lesions

Fuzzy rule extraction by bacterial memetic algorithms

Comparison of fuzzy rule-based learning and inference systems

CONDITION ASSESSMENT OF SIDE CORRIDORS WITH THE USE OF AGGREGATIONS BASED ON FUZZY INFERENCE METHOD

Application of Fuzzy Theory to Investigate the Effect of Innovation Power in the Emergence of an Advanced Reusable Packaging System

Fuzzy flip-flop based neural network as a function approximator

Experimenting with a new population-based optimization technique: FUNgal growth inspired (FUNGI) optimizer

Fuzzy solution for non-linear quality models

Fuzzy signature based mobil robot motion control system

Fuzzy rule base extraction by the improved bacterial memetic algorithm

Notes on the Dynamics of Hyperbolic Tangent Fuzzy Cognitive Maps

Intelligent Traffic Signal Control Using Rule Based Fuzzy System

Fuzzy flip-flops and neural nets?

Fuzzy extension for Kano's model using bacterial evolutionary algorithm

Experiments with the Discrete Bacterial Memetic Evolutionary Algorithm for Solving the Cumulative Capacitated Vehicle Routing Problem

Fuzzy Inference System-like Aggregation Operator for Fuzzy Signatures

Symmetry or Asymmetry? Complex Problems and Solutions by Computational Intelligence and Soft Computing

Separated antecedent and consequent learning for Takagi-Sugeno fuzzy systems

Fuzzy models, identification and applications

Fuzzy rule interpolation for multidimensional input spaces with applications: A case study

A Combined Approach of Fuzzy Cognitive Maps and Fuzzy Rule-Based Inference Supporting Freeway Traffic Control Strategies †

Extension of the Time Dependent Travelling Salesman Problem with Interval Valued Intuitionistic Fuzzy Model Applying Memetic Optimization Algorithm

Parameterization and concept optimization of FCM models

A hybrid discrete bacterial memetic algorithm with simulated annealing for optimization of the flow shop scheduling problem

Criticality analysis of purchased materials based on fuzzy signatures

Combining fuzzy signature and rough sets approach for predicting the minimum passing level of competency achievement

Three level fuzzy signature based decision methodology for packaging system design

Comparison of Discrete Memetic Evolutionary Metaheuristics for TSP

Forward and backward fuzzy rule base interpolation using fuzzy geometry

Local Binary Pattern-Based Fingerprint Matching