F. Hatwágner

15065328500

Publications - 39

Model Reduction Methods

F. Hatwágner

Publication Name: Studies in Fuzziness and Soft Computing

Publication Date: 2024-01-01

Volume: 427

Issue: Unknown

Page Range: 45-69

Description:

Fuzzy Cognitive Maps are very useful tools primarily in decision making and management tasks. They represent the main factors, variables of a complex system and the internal causal relationships among them in a straightforward way. Simulations can be started with an initial state, and the future states of the system under investigation can be predicted. This way, what-if questions can be answered. If the model of a system is created by experts they are often tempted to include too many components, because they are not sure in the importance of them. An oversized model is excruciating to use in practice, however. Model reduction methods help to decrease model size but unavoidably cause information loss as well. This effect does not cause a problem in practical decision making applications if the model suggests the same decisions. This chapter covers three FCM model reduction methods, their theoretical background and behavioral properties.

Open Access: Yes

DOI: 10.1007/978-3-031-37959-8_5

Introduction to Fuzzy Cognitive Maps

F. Hatwágner

Publication Name: Studies in Fuzziness and Soft Computing

Publication Date: 2024-01-01

Volume: 427

Issue: Unknown

Page Range: 1-13

Description:

This chapter gives a short introduction to Fuzzy Cognitive Maps (FCMs). It starts with the origin and first applications of Cognitive Maps, then describes the theoretical background of FCMs. Based on the cognitive model, simulations can be performed in order to predict the dynamic behavior of the system and support decision making tasks. The widely applied variations of implementation details are also covered, including their effect on model properties and behavior. A simple example is given to help understanding the theoretical parts, and a short outlook is provided to the possible ways of model creation, too.

Open Access: Yes

DOI: 10.1007/978-3-031-37959-8_1

Behavioral Analysis of Fuzzy Cognitive Maps

F. Hatwágner

Publication Name: Studies in Fuzziness and Soft Computing

Publication Date: 2024-01-01

Volume: 427

Issue: Unknown

Page Range: 81-93

Description:

In this Chapter, we will discuss two further case studies, namely, problems that were proposed by a French bank. Our team was involved by the request of a French university, and we started to collaborate with their respective team, experts in management topics. The bank put up several models, but unfortunately the real-world equivalent of most models, the modeled system, remained unknown to us because of trade secrets. This made it difficult or impossible to determine the correctness of the models and fine-tune their settings in order to make their behavior more similar to reality. There was only one exception regarding the management system of the bank. The concepts of it were identified by themselves and the French specialist team, and experts have estimated the mutual influence strengths and directions of these components on each other. Models created this way unavoidably contain more or less subjective elements, but even if the models had been produced by machine learning, their thorough investigation is recommended before usage. Sometimes a subtle modification of connection weights or a different λ parameter in the threshold function can result in a model that behaves significantly different. This chapter describes a method to automatically investigate a model and detect if some of its components affect its dynamic behavior significantly. Two models were selected from those developed by the bank to illustrate the method and the results obtained with it.

Open Access: Yes

DOI: 10.1007/978-3-031-37959-8_7

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

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 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

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

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

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

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

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

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

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

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

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

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

A study on solving single stage batch process scheduling problems with an evolutionary algorithm featuring bacterial mutations

F. Hatwágner Máté Hegyháti O. Ooz

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: 10841 LNAI

Issue: Unknown

Page Range: 386-394

Description:

The short term scheduling of batch processes is an active research field of chemical engineering, that has been addressed by many different techniques over the last decades. These approaches, however, are unable to solve long-term scheduling problems due their size, and the vast number of discrete decisions they entail. Evolutionary algorithms already proved to be efficient for some classes of large scheduling problems, and recently, the utilization of bacterial mutations has shown promising results on other fields. In this paper, an evolutionary algorithm featuring bacterial mutation is introduced to solve a case study of a single stage product scheduling problem. The solution performance of the algorithm was compared to a method from the literature. The results indicate that the proposed approach can find the optimal solution under relatively short execution times.

Open Access: Yes

DOI: 10.1007/978-3-319-91253-0_36

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Comparative analysis of parallel gene transfer operators in the bacterial evolutionary algorithm

F. Hatwágner Andras Horvath

Publication Name: Acta Polytechnica Hungarica

Publication Date: 2012-09-18

Volume: 9

Issue: 4

Page Range: 65-84

Description:

The Bacterial Evolutionary Algorithm (BEA) is an evolutionary method, originally meant to optimize the parameters of fuzzy systems. The authors have already proposed three modified versions of the original algorithm in a previous paper to make it usable in engineering applications with time-consuming object functions as well. Section 1 summarizes the earlier results. It presents the operators of the original BEA and the suggested parallel version. In Section 2, the optimal parameter settings and the analytical estimation of wall clock time in parallel computations are investigated. In Section 3, the paper deals with genetic diversity in different BEA versions. The effect of the modified gene transfer operators on genetic diversity is measured. The conclusion is that the proposed methods have quite good efficiency in all cases, and we can reach the ideal case if we have full control over the parameters.

Open Access: Yes

DOI: DOI not available

Searching for a nonlinear ODE model of vehicle crash with genetic optimization

F. Hatwágner István Harmati Andras Horvath

Publication Name: Saci 2012 7th IEEE International Symposium on Applied Computational Intelligence and Informatics Proceedings

Publication Date: 2012-01-01

Volume: Unknown

Issue: Unknown

Page Range: 131-136

Description:

Vehicle crash is a very complex process, which can be modelled in details using the finite element method (FEM), but a simple, quasi-heuristic model with a limited number of parameters is often more beneficial. In this paper we propose a relatively simple dynamic model for deformation and force during a frontal collision process, which has very similar behavior to the experimental data. A genetic-type optimization of model parameters is executed on three car crash experimental data sets. ©2012 IEEE.

Open Access: Yes

DOI: 10.1109/saci.2012.6249990

Error handling techniques of genetic algorithms in parallel computing environment

F. Hatwágner Andras Horvath

Publication Name: Pollack Periodica

Publication Date: 2008-08-01

Volume: 3

Issue: 2

Page Range: 3-14

Description:

It is easy to create parallel genetic algorithm software with master-slave type paralelization on a cluster of workstations. In a real situation the probability of errors in communication or in some of the slave processes during a long calculation is significant. In this paper we deal with different error handling strategies in master-slave type paralelization of standard GA algorithms and show results of test calculations. Our simulations are close to real applications in the sense that we examine the best achieved objective function value at a fixed wall clock time with different error handling strategies depending on the probability of errors and number of processors. Using these results we make suggestions on the selection of a good error handling method in different optimization problems. © 2008 Akadémiai Kiadó.

Open Access: Yes

DOI: 10.1556/Pollack.3.2008.2.1

The effect of computer network errors on genetic algorithms

F. Hatwágner Andras Horvath

Publication Name: Pollack Periodica

Publication Date: 2007-08-01

Volume: 2

Issue: 2

Page Range: 3-12

Description:

Genetic algorithms are widely used in engineering, to solve nonlinear, multi-target optimization problems with multiple variables (e.g. optimization of geometry of flow domains, parameters of control systems). The parallelization of software using genetic algorithms is very important because in a typical practical problem they need huge computational power. Fortunately it is easy to implement a master-slave style parallelization. Our goal was to investigate the effect of random errors that can occur in a cluster of workstations on the efficiency of the genetic algorithm. © 2007 Akadèmiai Kiadó.

Open Access: Yes

DOI: 10.1556/Pollack.2.2007.2.1

Design and implementation of Enum-based services

F. Hatwágner T. Heckenast Á Varga N. Varjasi Balázs Benyó K. Kovács

Publication Name: Journal of Universal Computer Science

Publication Date: 2006-11-23

Volume: 12

Issue: 9

Page Range: 1128-1138

Description:

ENUM is a technology based on a procedure that assigns a sequence of traditional telephone numbers to Internet domain names. It specifies a rule that makes it possible to relate a domain to a telephone number without any risk of ambiguity. This domain can then be used to identify various communication services like fax, mobile phone numbers, voice-mail systems, e-mail addresses, IP telephone addresses, web pages, OPS coordinates, call diverts or unified messaging. In our paper we deal with three main problem areas in connection with the business model of the ENUM service and with the introduction of new services, i.e. the questions of tariffs, legal regulations and financial return. For the ENUM procedure to spread out in use specific services have to be implemented that can exploit the advantages of the ENUM and efficient methods have to be elaborated to base existing services on ENUM. We will outline the two new services invented by our group and that we have implemented in our project. © J.UCS.

Open Access: Yes

DOI: DOI not available

Novel communication services based on ENUM technology

F. Hatwágner T. Heckenast Á Varga N. Varjasi Balázs Benyó K. Kovács

Publication Name: Ines 05 IEEE 9th International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2005-01-01

Volume: 2005

Issue: Unknown

Page Range: 217-220

Description:

ENUM is the short name for a protocol for connecting resources of telecommunication and the Internet to one another. It specifies a rule that makes it possible to relate a domain to a telephone number without any risk of ambiguity. This domain can then be used to identify various communication services like fax, mobile radio, voice-mail systems, e-mail addresses, IP telephony addresses, web pages, GPS coordinates, call diverts or unified messaging. Several countries in the world examine the possibilities of the use of ENUM in national trials. Recently two Hungarian universities and an Internet service provider established a research project aiming the development of ENUM based communication services. In Hungary we have to deal not only with the questions of creating and providing the technological background, but also with the business aspects of ENUM based service development. The article will firstly give an overview about the ENUM itself. Then it will deal with ENUM services and business models. After that we discuss the situation of ENUM in different European countries. It will present the planned and accomplished ENUM based services in these countries. Then we are going to give the aims of the project in Hungary, which is led by the Szechenyi Istvan University in Gy6r. In setting these aims we can rely on the projects of other countries, and learn from them. © 2005 IEEE.

Open Access: Yes

DOI: 10.1109/INES.2005.1555160