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Introduction
Interests: fuzzy sytems,optimisation, fuzzy rule extraction and model fitting by population based meta-heuristics.
Projects: Fuzzy communication and collaboration of intelligent robots, evaluation of telecommunication end-connections by fuzzy rules and wavelet transformation, Modeling management systems by fuzzy cognitive maps, Evaluation of objects and renovation planning by fuzzy signatures and fs state machines, Discrete optimisation by meta-heuristics (traveling salesman, bin-packing, etc.).
Current institution
Additional affiliations
September 2015 - November 2015
March 2014 - March 2014
January 1998 - March 2000
Education
January 1997 - January 1998
September 1987 - November 1989
September 1975 - June 1977
Publications
Publications (525)
This paper presents an innovative environment representation technique for mobile robots, incorporating obstacle detection within their operational space. Leveraging the fuzzy signature method, this approach uses quadtrees for efficient data organization. A set of fuzzy rules evaluates feature points to ascertain the relevance of identified obstacl...
Traffic congestion is a universal problem that significantly impacts urban mobility and economic productivity. Accurate traffic flow prediction is crucial for efficient traffic management and congestion mitigation. Traditional methods often struggle to capture the complex temporal dependencies in traffic data. This study explores the effectiveness...
This paper presents a Mamdani fuzzy inference system (FIS) designed for predicting tennis match outcomes with greater accuracy compared to existing models such as the Weighted Elo (WElo) ranking system. By integrating factors like historical performance, surface-specific proficiency, and recent form trends, the Mamdani FIS provides a nuanced approa...
Fuzzy signatures have demonstrated effectiveness in various knowledge-representation domains, including medical decision-making systems and complex decision-making tasks across numerous fields. Even though the advancements in the field of fuzzy signatures have been substantial, the complete potential for developing a comprehensive graph-theoretical...
Assessing fine motor skills (FMS) in early school-age children is crucial for insights into their school readiness. In many countries, including Indonesia, teachers assess FMS by observing handwriting, often with the aid of an educational psychologist. However, this approach can be subjective and prone to observer bias. This study aimed to classify...
![Architecture of three-stage fuzzy controller with four modules [25].](publication/387575615/figure/fig1/AS:11431281415908236@1746053989670/Architecture-of-three-stage-fuzzy-controller-with-four-modules-25_Q320.jpg)
Traffic congestion at a single intersection can propagate and thus affect adjacent intersections as well, potentially resulting in prolonged gridlock across an entire urban area. Despite numerous research efforts aimed at developing intelligent traffic signal control systems, urban areas continue to experience traffic congestion. This paper present...
Sensing has become a pivotal element in the development of autonomous systems with the advancement of the technology. These systems operate on a sense-think-act cycle to execute tasks, necessitating the integration of multiple sensors. The challenge of synthesizing meaningful information from diverse data sources escalates with the complexity of th...
In this paper, we address the challenge of creating candidate sets for large-scale Traveling Salesman Problem (TSP) instances, where choosing a subset of edges is crucial for efficiency. Traditional methods for improving tours, such as local searches and heuristics, depend greatly on the quality of these candidate sets but often struggle in large-s...
![Architecture of a three-stage fuzzy traffic control system [27].](publication/383872123/figure/fig1/AS:11431281388217788@1745163581085/Architecture-of-a-three-stage-fuzzy-traffic-control-system-27_Q320.jpg)
In this study, the concept of symmetry is employed to implement an intelligent fuzzy traffic signal control system for complex intersections. This approach suggests that the implementation of reduced fuzzy rules through the reduction method, without compromising the performance of the original fuzzy rule base, constitutes a symmetrical approach. In...
This research introduces an innovative approach for End-to-End steering angle prediction and its control in electric power steering (EPS) systems. The methodology integrates transfer learning-based computer vision techniques for prediction and control with fuzzy signatures-enhanced fuzzy systems. Fuzzy signatures are unique multidimensional data st...
Clustering technics, like k-means and its extended version, fuzzy c-means clustering (FCM) are useful tools for identifying typical behaviours based on various attitudes and responses to well-formulated questionnaires, such as among forensic populations. As more or less standard questionnaires for analyzing aggressive attitudes do exist in the lite...
Efficient management of mainstream traffic flow on freeway networks is a critical challenge in urban transportation, with significant implications for congestion mitigation and environmental sustainability. The purpose of this study is to address the problem of predicting traffic volumes and maintaining flow rates below critical densities, thereby...
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 wa...
Despite the rapid development of the automated fingerprint identification system, some challenging fields need more enhancement. Typically, fingerprints suffer from distortion, partial cuts, and noise, making the identification process uncertain and more probabilistic. In this research, we aim to improve the fingerprint identification system using...
Routing optimization nowadays is an important and popular topic, it plays a key role in the transport and logistics industry. In this paper we present a software tool for solving the Traveling Salesman Problem and related non-fuzzy and fuzzy optimization problems. For this purpose the Discrete Bacterial Memetic Evolutionary Algorithm (DBMEA) was im...
Problem
The frequency of liver cancer is rising worldwide, and it is a common, deadly condition. For successful treatment and patient survival, early and precise diagnosis is essential. The automated classification of liver cancer using medical imaging data has shown potential outcome when employing machine and deep learning (DL) approaches. To tra...
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...
Flow-shop scheduling problems are classic examples of multi-resource and multi-operation scheduling problems where the objective is to minimize the makespan. Because of the high complexity and intractability of the problem, apart from some exceptional cases, there are no explicit algorithms for finding the optimal permutation in multi-machine envir...
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...
Over the past decades, there has been an ever-increasing saturation of traffic networks due to the growing number of road vehicles, and due to the available limited. To solve these problems, adaptive, (semi-) intelligent traffic control has been used widely for the last decades. These systems nevertheless, have some shortages, the most obvious one...
Fuzzy rule interpolation (FRI) predicts an accountable outcome of a possible course of action in sparse fuzzy rule base
system (FRBS). The geometry based linear fuzzy rule interpolation (GLFRI) is extended for multi-dimensional fuzzy
rule base interpolation. Expansion/contraction (EC) of triangular, trapezoidal and complex polygonal fuzzy sets has...
![Modeling freeway traffic approaches [6].](publication/365153287/figure/fig2/AS:11431281416132076@1746052816201/Modeling-freeway-traffic-approaches-6_Q320.jpg)
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 scheduling of jobs in functional production systems (Job shop scheduling) is a frequently researched area of the literature. However, the management of material handling in functional production systems receives little attention. Publications in connection with that can scarcely be found, even though in the case of small and medium-sized compan...
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 Fuz...
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...
In this paper we present our initial experiments with the Discrete Bacterial Memetic Evolutionary Algorithm for solving the Cumulative Capacitated Vehicle Routing Problem. The algorithm was tested on instances proposed in the literature. However our method was able to find the optimal solution for small (around 50 nodes) instances, but its converge...
What is the role of symmetry in the seemingly far away topics of solving complex applied problems by approaches offered by Soft Computing and Computational Intelligence [...]
![Fuzzy signature structure according to [9].](publication/362723374/figure/fig4/AS:11431281415964143@1746049578839/Fuzzy-signature-structure-according-to-9_Q320.jpg)
Similarity between two fuzzy values, sets, etc., may be defined in various ways. The authors here attempt introducing a general similarity measure based on the direct extension of the Boolean minimal form of equivalence operation. It is further extended to hierarchically structured multicomponent fuzzy signatures. Two versions of this measure, one...
Hybrid vehicles are gaining increasing global prominence, especially in the military, where unexpected breakdowns or even power deficits are not only associated with greater expense but can also cost the lives of military personnel. In some cases, it is extremely important that all battery cells and modules deliver the specified amount of capacity....
The aim of the present paper is to develop an integrated method that provides assistance to decision makers during packaging system planning, design, operation and evaluation from an environmental perspective. The role of the packaging system is to provide a cover for the handling and communication functions surrounding the product. Single-use and...
In this paper we analyze the efficiency of three TSP solver methods: the best-performing exact Concorde algorithm, the state-of-the-art inexact Helsgaun’s Lin–Kernighan heuristic and our Discrete Bacterial Memetic Evolutionary Algorithm (DBMEA). In our analysis the run time predictability was also taken into account, not only the tour quality and t...
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 req...
In our paper we compare discrete memetic evolutionary metaheuristics (and other algorithms) which are applicable (also) for the widely studied and industrially applied (symmetric, Euclidean) NP-hard combinatorial optimization problem called Traveling Salesman Problem (TSP) such as DBMEA (Discrete Bacterial Memetic Evolutionary Algorithm), DMTLBO (D...
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 t...
Fuzzy cognitive maps are recurrent neural networks, applied for modelling and simulation of complex dynamic systems. They have been successfully applied to many engineering problems. The conclusion about the system depends on the mathematical behaviour of an iteration, namely, a first-order recursion. The first-order dynamics have some limitations...
Various Optical Character Recognition (OCR) methods, especially, machine learning models, work towards the solution of recognizing patterns in intelligent ways from data that is originally not available in digital format. These patterns are converted into data that a machine can recognize (by the proper algorithm) and can further manipulate for var...
In this paper we propose an image-based fingerprint recognition system. The method is based on Local Binary Pattern features extracted from the region of the fingerprint image around the core point. The experiments on the FVC2002 fingerprint databases show the effectiveness of the proposed approach.
Complex problems and systems, which prevail in the real world, cannot often be tackled and solved either by traditional methods offered by mathematics or even the traditional computer science (CS) and and artificial intelligence (AI)..). What is the way out of this dilemma? Advanced methodologies, and tools and techniques, „mimicking” human reasoni...
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...
There are many factors that affect the performance of the evolutionary and memetic algorithms. One of these factors is the proper selection of the initial population, as it represents a very important criterion contributing to the convergence speed. Selecting a conveniently preprocessed initial population definitely increases the convergence speed...
The process of traffic control systems significantly relies on the immediate detection of breakdown states. As a result of their crisp (non-fuzzy) based calculation procedures, conventional traffic estimators and predictors cannot effectively model traffic states. In fact, these methods are characterized by exact features, while traffic is defined...
![Proven upper bounds on parameter λ\documentclass[12pt]{minimal}...](publication/357004532/figure/fig4/AS:1100781709201410@1639458219757/Proven-upper-bounds-on-parameter-ldocumentclass12ptminimal-usepackageamsmath_Q320.jpg)
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...
![Fig. 1 A schematic illustration of simple FCM [7]](profile/Mehran-Amini/publication/356645763/figure/fig1/AS:1097449292742656@1638663709099/A-schematic-illustration-of-simple-FCM-7_Q320.jpg)
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, t...
The increase of the classification accuracy level has become an important problem in machine learning especially in diverse data-set that contain the outlier data. In the data stream or the data from sensor readings that produce large data, it allows a lot of noise to occur. It makes the performance of the machine learning model is disrupted or eve...
This paper deals with the flow shop scheduling problem. To find the optimal solution is an NP-hard problem. The paper reviews some algorithms from the literature and applies a benchmark dataset to evaluate their efficiency. In this research work, the discrete bacterial memetic evolutionary algorithm (DBMEA) as a global searcher was investigated. Th...
This paper presents a novel approach to mobile robot environment representation to hold information on detected obstacles. The method is inspired by fuzzy signature-based formalism and is based on classical quadtrees as a data indexing structure. Each detected feature point is evaluated by a fuzzy-ruleset defining the presumed significance of each...
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 ef...
The creation of the initial population is an essential part of the population based evolutionary algorithms. An appropriate initial population could lead to much faster convergence speed; in contrast, an inappropriate initial population could even cause getting stuck in a local optimum. In this paper, we will propose a new efficient heuristic metho...
In the following study the effects of two image preprocessing methods, namely Gaussian filtering and Wiener filtering, is studied on the results of a fuzzy inference method previously developed by the authors, for determining whether a colonoscopy picture segment contains any colorectal polyp. As earlier results show that less blurry, less compress...
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-redu...
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...
In our fast-growing world, we need to create increasingly efficient systems to ensure further growth and sustainability. This also applies to transportation, where a key limitation is the bottle-necks of road network capacity. To eliminate, or at least, to moderate these bottlenecks, they must first be localised. In this case study, a model is prop...
Fuzzy signatures have been used for various applications, including medical diagnosis, communication of robots based on intention guessing, and residential building evaluation. However, there exist many questions about this research topic which have not been addressed in the literature. One of the most important aims is to formally define a family...
Globalization and its challenges for organizations led to the understanding that employees can be a critical factor contributing to the organization’s performance. Therefore, various studies sought to understand employee’s behaviour that in itself encompasses various forms of engagement. One of the constructs defining engagement is citizenship beha...
Atanassov’s intuitionistic fuzzy set (IFS) described the uncertainty of real-life events with the help of a membership and a non-membership degree. However, human opinion cannot be restricted to yes or no but there is some abstinence and refusal degree as well. In such cases, picture fuzzy set (PFS) is a suitable solutioin which described the absti...
The Traveling Salesman Problem (TSP) is a well-known combinatorial optimization problem. There are many different extensions and modifications of the original problem, such as The Time Dependent Traveling Salesman Problem (TDTSP), this specific extension of the original TSP towards more realistic traffic conditions assessment. In TDTSP the "distanc...
In modern logistics, companies and packaging engineers have to make decisions to find the optimal sustainable product-packaging system with adequate protection. The decision most often involves a decision option between disposable (single-trip) and reusable (returnable) packaging solutions. In practice, in most cases, this decision is based on hist...
Fuzzy cognitive maps are recurrent neural networks, where the neurons have a well-defined meaning. In certain models, some neurons receive outer input, while other neurons produce the output of the system. According to this observation, some neurons are categorized as input neurons and the others are the state neurons and output neurons. The output...
This study compares three fuzzy based model approaches for solving a realistic extension of the Time Dependent Traveling Salesman Problem. First, the triple Fuzzy (3FTD TSP) model, where the uncertain costs between the nodes depend on time are expressed by fuzzy sets. Second, the intuitionistic fuzzy (IFTD TSP) approach, where including hesitation...
Fuzzy grey cognitive maps (FGCMs) are extensions of fuzzy cognitive maps (FCMs), where the causal connections between the concepts are represented by so-called grey numbers. Just like in classical FCMs, the inference is determined by an iteration process, which may converge to an equilibrium point, but limit cycles or chaotic behaviour may also sho...
In this paper we revisit the memetic evolutionary family of metaheuristics, called Discrete Bacterial Memetic Evolutionary Algorithm (DBMEA), whose members combine Furuhashi's Bacterial Evolutionary Algorithm and various discrete local search techniques. These algorithms have proven to be efficient approaches for the solution of NP-hard discrete op...
This study proposes a new model and approach for solving a realistic extension of the Time-Dependent Traveling Salesman Problem, by using the concept of distance between interval-valued intuitionistic fuzzy sets. For this purpose, we developed an interval-valued fuzzy degree repository based on the relations between rush hour periods and traffic re...
The evaluation of data obtained from responses given to questionnaires in humanities and social sciences, such as management, linguistics, etc. is a complex task with the necessity of dealing with the inherent subjectivity and vagueness in such data. In this paper, a method based on fuzzy signatures (FSigs), suitable for analyzing questionnaires wi...
The Traveling Salesman Problem (TSP) is an NP-hard graph search problem. Despite having numerous modifications of the original abstract problem, Time Dependent Traveling Salesman Problem (TD TSP) was one of the most realistic extensions under real traffic conditions. In TD TSP the edges between nodes are assigned higher costs (weights), if they wer...
Fuzzy grey cognitive maps (FGCMs) are extensions of fuzzy cognitive maps (FCMs), applying uncertain weights between the concepts. This uncertainty is expressed by so-called grey numbers. Similarly to FCMs, the inference is determined by an iteration process, which may converge to an equilibrium point, but limit cycles or chaotic behaviour may also...
In this paper we present our test results with our memetic algorithm, the Discrete Bacterial Memetic Evolutionary Algorithm (DBMEA). The algorithm combines the Bacterial Evolutionary Algorithm with discrete local search techniques (2-opt and 3-opt).
In the field of logistics packaging (industrial-, or even customer packaging), companies have to take decisions on determining the optimal packaging solutions and expenses. The decisions often involve a choice between one-way (disposable) and reusable (returnable) packaging solutions. Even nowadays, in most cases the decisions are made based on tra...
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 re...
Residential buildings can be qualified and ranked based on many viewpoints. For the intervening decision-supporting survey of old residential buildings in the course of our former researches we have created a fuzzy signature based model which defines status evaluation and ranking of buildings on the basis of the condition of load-bearing structures...
In the measurement of microgeometrical surfaces it is useful if the same location can be found on a surface for two or more different and independent measurements, as in this case not only statistical parameters of the measurements can be compared, but direct differences can be calculated. Honing is a typical surface processing method resulting in...
In the field of logistics packaging (industrial-, or even customer packaging), companies have to take decisions on determining the optimal packaging solutions and expenses. The decisions often involve a choice between one-way (disposable) and reusable (returnable) packaging solutions. Even nowadays, in most cases the decisions are made based on tra...
Fuzzy Cognitive Maps are network-like decision support tools, where the final conclusion is determined by an iteration process. Although the final conclusion relies on the assumption that the iteration reaches a fixed point, it is not straightforward that the iteration will converge to anywhere, since it can produce limit cycles or chaotic behaviou...
A set of answers to questions to employees of various companies in Lithuania may refer to various positive and negative aspects of the attitudes of employees. These are called Organizational Citizenship Behavior (positive) and Counterproductive Work Behavior (negative). The components in the answers may be grouped by expert knowledge, and by statis...
Questions
Questions (3)
We are editing a special issue of the Complexity journal (Wiley and Hindawi, IF>3.5) on Computational Intelligence in Modeling Complex Systems and Solving Complex Problems, with my fellow Guest Editors Marek Reformat, Jesus Medina, Kevin Wong and Jin Hee Yoon. The call for papers may be found here: https://www.hindawi.com/journals/complexity/osi/ . Although Complexity is an open access journal with Article Processing Charges, manuscripts submitted from countries under a waiver (see the list here https://www.hindawi.com/waiver/) are free of any charges - even if other authors come from countries which are not exempted. We would be happy if you submitted your manuscript by the deadline indicated in the Call. In the meantime, Reserach Gate is a good forum to discuss whether a certain research result fits in the area of the special issue, and also to team up with related research in international groups - maybe including countries which are under the waiver. I look forward to your suggestions and ideas in connection with research relevant for the topic of the special issue!
Can you construct a fuzzy rule base If y is B then x is A from a rule base If x is A then y is B? What is the condition for an inverse (or quasi inverse) existing?
The combination of bacterial evolutionary optimization with gradient type local search (e.g. steepest descent or Levenberg-Marquardt) usually produces better results than simple evolutionary approaches. What might be the reason for some "outlier" data sets where the local search does not help, and why might Particle Swarm Optimization outperform Bacterial Evolutionary Algorithm for exceptional cases? We used benchmark data sets from the KEEL data repository. For lower dimensions but fuzzy constraints we found such an "abnormal" behavior.
