Ferenc Lilik

55670792200

Publications - 28

A Systematic Analysis of Neural Networks, Fuzzy Logic and Genetic Algorithms in Tumor Classification

Ferenc Lilik Ahmed Al-Ashoor Szilvia Nagy

Publication Name: Applied Sciences Switzerland

Publication Date: 2025-05-01

Volume: 15

Issue: 9

Page Range: Unknown

Description:

This study explores existing research on neural networks, fuzzy logic-based models, and genetic algorithms applied to brain tumor classification. A systematic review of 53 studies was conducted following PRISMA guidelines, covering search strategy, selection criteria, quality assessment, and data extraction. Articles were collected from three scientific databases: Web of Science, Scopus, and IEEE. The review primarily focuses on practical contributions, with most studies emphasizing applications over conceptual insights. Key methods in the field demonstrate significant impact and innovation. Commonly used training and testing mechanisms include dataset splitting, augmentation, and validation techniques, highlighting their widespread adoption for performance evaluation. The analysis of evaluation metrics shows that accuracy and the DICE score are the most frequently used, alongside sensitivity, specificity, recall, and other domain-specific measures. The variety of metrics underscores the need for tailored approaches based on dataset characteristics and research objectives. By highlighting trends, challenges, and research gaps, this review provides actionable insights for advancing BTC research. It offers a comprehensive overview of techniques and evaluation methods to guide future developments in this critical domain.

Open Access: Yes

DOI: 10.3390/app15095186

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

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

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

On Selecting, Ranking, and Quantifying Features for Building a Liver CT Diagnosis Aiding Computational Intelligence Method

Ferenc Lilik Melinda Kovacs Szilvia Nagy

Publication Name: Applied Sciences Switzerland

Publication Date: 2023-03-01

Volume: 13

Issue: 6

Page Range: Unknown

Description:

Featured Application: The selected attributes and their ranking and weights can be used in decision support algorithms in computer aided diagnosis. The liver is one of the most common locations for incidental findings during abdominal CT scans. There are multiple types of disease that can arise within the liver and many of them are nodular. The ultimate goal of our research is to develop an expert knowledge-based system using fuzzy signatures, to support decisions during diagnosis of the most frequent of these nodular lesions. Since the literature contains limited information about the graphical properties of CT images that must be taken into consideration and their relationship to one another, in this paper we focused on selecting and ranking the input parameters using expert knowledge and determining their importance. Six visual attributes of lesions (size, shape, density, homogeneity contour, and other features) were selected based on textbooks of radiology and expert opinion. The importance of these attributes was ranked by radiologist experts using questionnaires and a pairwise comparison technique. The most important feature was found to be the density of the lesion on the various CT phases, and the least important was the size, the order of the other attributes was other features, contour, homogeneity, and shape, with a Kendall concordance coefficient of 0.612. Weights for the attributes, to be used in the future fuzzy signatures, were also determined. As a last step, several statistical parameter-based quantities were generated to represent the above abstract attributes and evaluated by comparing them to expert opinions.

Open Access: Yes

DOI: 10.3390/app13063462

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

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

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

Development of a Fuzzy Inference System Based Rapid Visual Screening Method for Seismic Assessment of Buildings Presented on a Case Study of URM Buildings

O. Kegyes-Brassai Ferenc Lilik Nurullah Bektaş

Publication Name: Sustainability Switzerland

Publication Date: 2022-12-01

Volume: 14

Issue: 23

Page Range: Unknown

Description:

Many conventional rapid visual screening (RVS) methods for the seismic assessment of existing structures have been designed over the past three decades, tailored to site-specific building features. The objective of implementing RVS is to identify the buildings most susceptible to earthquake-induced damage. RVS methods are utilized to classify buildings according to their risk level to prioritize the buildings at high seismic risk. The conventional RVS methods are employed to determine the damage after an earthquake or to make safety assessments in order to predict the damage that may occur in a building before an impending earthquake. Due to the subjectivity of the screener based on visual examination, previous research has shown that these conventional methods can lead to vagueness and uncertainty. Additionally, because RVS methods were found to be conservative and to be partially accurate, as well as the fact that some expert opinion based developed RVS techniques do not have the capability of further enhancement, it was recommended that RVS methods be developed. Therefore, this paper discusses a fuzzy logic based RVS method development to produce an accurate building features responsive examination method for unreinforced masonry (URM) structures, as well as a way of revising existing RVS methods. In this context, RVS parameters are used in a fuzzy-inference system hierarchical computational pattern to develop the RVS method. The fuzzy inference system based RVS method was developed considering post-earthquake building screening data of 40 URM structures located in Albania following the earthquake in 2019 as a case study. In addition, FEMA P-154, a conventional RVS method, was employed to screen considered buildings to comparatively demonstrate the efficiency of the developed RVS method in this study. The findings of the study revealed that the proposed method with an accuracy of 67.5% strongly outperformed the conventional RVS method by 42.5%.

Open Access: Yes

DOI: 10.3390/su142316318

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

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

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

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

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

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

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 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

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

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

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

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

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

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

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

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

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

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

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