TY - CHAP AU - Amini, Mehran AU - Hatwágner, F. Miklós AU - Kóczy, T. László ED - Szakál, Anikó TI - Machine learning and fuzzy cognitive maps in a hybrid approach toward freeway on-ramp traffic control T2 - IEEE 17th International Symposium on Applied Computational Intelligence and Informatics SACI 2023 : Proceedings PB - IEEE Hungary Section CY - Budapest SN - 9798350321104 PY - 2023 SP - 000587 EP - 000592 PG - 6 DO - 10.1109/SACI58269.2023.10158585 UR - https://m2.mtmt.hu/api/publication/34043590 ID - 34043590 N1 - Export Date: 31 July 2023 Correspondence Address: Amini, M.; Szechenyi Istvan University, Hungary; email: mehran@sze.hu LA - English DB - MTMT ER - TY - JOUR AU - Harmati, István Árpád AU - Hatwágner, F. Miklós AU - Kóczy, T. László TI - Global stability of fuzzy cognitive maps JF - NEURAL COMPUTING & APPLICATIONS J2 - NEURAL COMPUT APPL VL - 35 PY - 2023 IS - 10 SP - 7283 EP - 7295 PG - 13 SN - 0941-0643 DO - 10.1007/s00521-021-06742-9 UR - https://m2.mtmt.hu/api/publication/32545090 ID - 32545090 LA - English DB - MTMT ER - TY - CHAP AU - Amini, Mehran AU - Hatwágner, F. Miklós AU - Kóczy, T. László ED - Ciucci, Davide ED - Couso, Inés ED - Medina, Jesús ED - Ślęzak, Dominik ED - Petturiti, Davide ED - Bouchon-Meunier, Bernadette ED - Yager, Ronald R TI - Fuzzy System-Based Solutions for Traffic Control in Freeway Networks Toward Sustainable Improvement T2 - Information Processing and Management of Uncertainty in Knowledge-Based Systems: 19th International Conference, IPMU 2022 : Proceedings, Part II VL - 1602 CCIS PB - Springer International Publishing CY - Cham SN - 9783031089749 T3 - Communications in Computer and Information Science, ISSN 1865-0929 ; 1602. PY - 2022 SP - 288 EP - 305 PG - 18 DO - 10.1007/978-3-031-08974-9_23 UR - https://m2.mtmt.hu/api/publication/33049054 ID - 33049054 N1 - Department of Information Technology, Szechenyi Istvan University, Gyor, Hungary Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, Budapest, Hungary Export Date: 12 August 2022 Correspondence Address: Amini, M.; Department of Information Technology, Hungary; email: mehran@sze.hu LA - English DB - MTMT ER - TY - JOUR AU - Amini, Mehran AU - Hatwágner, F. Miklós AU - Kóczy, T. László TI - A Combined Approach of Fuzzy Cognitive Maps and Fuzzy Rule-Based Inference Supporting Freeway Traffic Control Strategies JF - MATHEMATICS J2 - MATHEMATICS-BASEL VL - 10 PY - 2022 IS - 21 PG - 17 SN - 2227-7390 DO - 10.3390/math10214139 UR - https://m2.mtmt.hu/api/publication/33272027 ID - 33272027 N1 - Department of Informatics, Szechenyi Istvan University, Gyor, 9026, Hungary Department of Telecommunication and Media Informatics, Budapest University of Technology and Economics, Budapest, 1111, Hungary Cited By :1 Export Date: 3 April 2023 Correspondence Address: Amini, M.; Department of Informatics, Hungary; email: mehran@sze.hu Correspondence Address: Koczy, L.T.; Department of Informatics, Hungary; email: koczy@tmit.bme.hu AB - 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. LA - English DB - MTMT ER - TY - CHAP AU - Hatwágner, F. Miklós AU - Kóczy, T. László ED - Moreno-García, Juan ED - Medina-Moreno, Jesús ED - Kóczy, T. László ED - Cornejo, María Eugenia TI - Novel Methods of FCM Model Reduction T2 - Computational Intelligence and Mathematics for Tackling Complex Problems 2 PB - Springer Cham CY - Cham SN - 9783030888169 T3 - Studies in Computational Intelligence, ISSN 1860-949X ; 955. PY - 2022 SP - 101 EP - 112 PG - 12 DO - 10.1007/978-3-030-88817-6_12 UR - https://m2.mtmt.hu/api/publication/32678952 ID - 32678952 N1 - Conference code: 271109 Export Date: 7 April 2022 Correspondence Address: Hatwágner, M.F.; Department of Information Technology, Hungary; email: miklos.hatwagner@sze.hu Funding details: Nemzeti Kutatási Fejlesztési és Innovációs Hivatal, NKFI, K108405, K124055 Funding text 1: The paper was written with the support of the project titled “Internationalisation, initiatives to establish a new source of researchers and graduates and development of knowledge and technological transfer as instruments of intelligent specialisations at Széchenyi István University” (project number: EFOP-3.6.1-16-2016-00017). M. F. H. acknowledges the financial support of the DE Excellence Program. L. T. K. is supported by NKFIH K108405 and K124055 grants. LA - English DB - MTMT ER - TY - JOUR AU - Amini, Mehran AU - Hatwágner, F. Miklós AU - Mikulai, Gergely Csaba AU - Kóczy, T. László TI - A vehicular traffic congestion predictor system using Mamdani fuzzy inference JF - SYSTEM THEORY CONTROL AND COMPUTING JOURNAL J2 - SYST THEORY CONTROL COMP J VL - 1 PY - 2021 IS - 2 SP - 49 EP - 57 PG - 9 SN - 2668-2966 DO - 10.52846/stccj.2021.1.2.27 UR - https://m2.mtmt.hu/api/publication/32556112 ID - 32556112 LA - English DB - MTMT ER - TY - JOUR AU - Amini, Mehran AU - Hatwágner, F. Miklós AU - Mikulai, Gergely Csaba AU - Kóczy, T. László TI - Developing a macroscopic model based on fuzzy cognitive map for road traffic flow simulation JF - INFOCOMMUNICATIONS JOURNAL J2 - INFOCOMM J VL - 13 PY - 2021 IS - 3 SP - 14 EP - 23 PG - 10 SN - 2061-2079 DO - 10.36244/ICJ.2021.3.2 UR - https://m2.mtmt.hu/api/publication/32537879 ID - 32537879 N1 - Department of Information Technology, Szechenyi Istvan University, Gyor, Hungary Doctoral School of Regional Sciences and Business Administration, Gyor, Hungary Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, Hungary Export Date: 18 January 2022 Correspondence Address: Amini, M.; Department of Information Technology, Hungary Funding details: National Research, Development and Innovation Office, NKFIH K124055 Funding text 1: This research was supported by the National Office of Research, Development, and Innovation grant NKFIH K124055. AB - 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. LA - English DB - MTMT ER - TY - JOUR AU - Hatwágner, F. Miklós AU - Kóczy, T. László TI - Stability of Fixed-Point Values in Reduced Fuzzy Cognitive Map Models JF - STUDIES IN FUZZINESS AND SOFT COMPUTING J2 - STUD FUZZ SOFT COMP VL - 393 PY - 2021 SP - 359 EP - 372 PG - 14 SN - 1434-9922 DO - 10.1007/978-3-030-47124-8_29 UR - https://m2.mtmt.hu/api/publication/31809177 ID - 31809177 LA - English DB - MTMT ER - TY - CHAP AU - Amini, Mehran AU - Hatwágner, F. Miklós AU - Mikulai, Gergely Csaba AU - Kóczy, T. László ED - Szakál, Anikó TI - An intelligent traffic congestion detection approach based on fuzzy inference system T2 - 15th IEEE International Symposium on Applied Computational Intelligence and Informatics SACI 2021 PB - Institute of Electrical and Electronics Engineers (IEEE) CY - Budapest CY - Piscataway (NJ) SN - 9781728195438 PY - 2021 SP - 97 EP - 104 PG - 8 DO - 10.1109/SACI51354.2021.9465637 UR - https://m2.mtmt.hu/api/publication/32101466 ID - 32101466 N1 - Funding Agency and Grant Number: National Research, Development and Innovation Office NKFIHNational Research, Development & Innovation Office (NRDIO) - Hungary [K124055] Funding text: This research was supported by the National Research, Development and Innovation Office NKFIH grant Nr. K124055. AB - 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. LA - English DB - MTMT ER - TY - CHAP AU - Hatwágner, F. Miklós AU - Kóczy, T. László ED - Dernóczy, Adrienn TI - A Novel Approach to Analyze the Behavior of Fuzzy Cognitive Maps T2 - Kutatási jelentés - Research Report, 2. kötet PB - Universitas-Győr Nonprofit Kft. CY - Győr T3 - Kutatási jelentés (Széchenyi István Egyetem, Győr), ISSN 2676-7937 ; 2. PY - 2020 SP - 351 EP - 356 PG - 6 UR - https://m2.mtmt.hu/api/publication/31430826 ID - 31430826 LA - English DB - MTMT ER - TY - JOUR AU - Ramirez-Bautista, Julian Andres AU - Huerta-Ruelas, Jorge Adalberto AU - Kóczy, T. László AU - Hatwágner, F. Miklós AU - Chaparro-Cárdenas, Silvia L. AU - Hernández-Zavala, Antonio TI - Classification of plantar foot alterations by fuzzy cognitive maps against multi-layer perceptron neural network JF - BIOCYBERNETICS AND BIOMEDICAL ENGINEERING J2 - BIOCYBERN BIOMED ENG VL - 40 PY - 2020 IS - 1 SP - 404 EP - 414 PG - 11 SN - 0208-5216 DO - 10.1016/j.bbe.2019.12.008 UR - https://m2.mtmt.hu/api/publication/31251813 ID - 31251813 N1 - Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada – Instituto Politécnico Nacional, Av. Cerro Blanco #141, Col. Colinas del Cimatario, Querétaro, Mexico Department of Information Technology, Széchenyi István University, Egyetem tér 1, Győr, 9026, Hungary Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, Műegyetem rkp. 3, Budapest, 1111, Hungary Cited By :9 Export Date: 5 September 2022 Correspondence Address: Hernández-Zavala, A.; Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada – Instituto Politécnico Nacional, Av. Cerro Blanco #141, Col. Colinas del Cimatario, Mexico; email: anhernandezz@ipn.mx LA - English DB - MTMT ER - TY - JOUR AU - Buruzs, Adrienn AU - Hatwágner, F. Miklós AU - Kóczy, T. László TI - Reduced Model Investigations Supported by Fuzzy Cognitive Map to Foster Circular Economy JF - STUDIES IN COMPUTATIONAL INTELLIGENCE J2 - STUD COMP INTELLIG VL - 796 PY - 2019 SP - 191 EP - 202 PG - 12 SN - 1860-949X DO - 10.1007/978-3-030-00485-9_22 UR - https://m2.mtmt.hu/api/publication/30326141 ID - 30326141 N1 - Megjelent a "Trends in Mathematics and Computational Intelligence" c. kötetben Department of Environmental Engineering, Széchenyi István University, Győr, Hungary Department of Information Technology, Széchenyi István University, Győr, Hungary Department of Automation, Széchenyi István University, Győr, Hungary Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, Budapest, Hungary Cited By :1 Correspondence Address: Buruzs, A.; Department of Environmental Engineering, Hungary; email: buruzs@sze.hu LA - English DB - MTMT ER - TY - CHAP AU - Hatwágner, F. Miklós AU - Vastag, Gyula AU - Niskanen, Vesa A. AU - Kóczy, T. László TI - Banking Applications of FCM Models T2 - Trends in Mathematics and Computational Intelligence PB - Springer Netherlands CY - Cham SN - 9783030004842 T3 - Studies in Computational Intelligence, ISSN 1860-949X ; 796. PY - 2019 SP - 61 EP - 72 PG - 12 DO - 10.1007/978-3-030-00485-9_7 UR - https://m2.mtmt.hu/api/publication/32749368 ID - 32749368 LA - English DB - MTMT ER - TY - CHAP AU - Andres, Ramirez-Bautista Julian AU - Hernandez-Zavala, Antonio AU - Huerta-Ruelas, Jorge A. AU - Hatwágner, F. Miklós AU - Chaparro-Cardenas, Silvia L. AU - Kóczy, T. László ED - Batyrshin, I ED - Villasenor, MDM ED - Espinosa, HEP TI - Detection of Human Footprint Alterations by Fuzzy Cognitive Maps Trained with Genetic Algorithm T2 - 2018 17TH MEXICAN INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE (MICAI 2018) PB - Institute of Electrical and Electronics Engineers (IEEE) CY - New York, New York SN - 9780769565927 T3 - Mexican International Conference on Artificial Intelligence-MICAI PY - 2018 SP - 32 EP - 38 PG - 7 DO - 10.1109/MICAI46078.2018.00013 UR - https://m2.mtmt.hu/api/publication/33079543 ID - 33079543 N1 - Funding Agency and Grant Number: Centro de Investigacion en Ciencia Aplicada y Tecnologia Avanzada, Queretaro unit, from Instituto Politecnico Nacional, Mexico; Consejo Nacional de Ciencia y Tecnologia (CONACyT) Mexico; PIEDICA center; Szechenyi Istvan University Funding text: The authors would thank to Centro de Investigacion en Ciencia Aplicada y Tecnologia Avanzada, Queretaro unit, from Instituto Politecnico Nacional, Mexico, the Consejo Nacional de Ciencia y Tecnologia (CONACyT) Mexico, PIEDICA center, and Szechenyi Istvan University, for their support in the realization of this work. AB - 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. LA - English DB - MTMT ER - TY - CHAP AU - Hatwágner, F. Miklós AU - Vastag, Gyula AU - Niskanen, V A AU - Kóczy, T. László ED - Rutkowski, Leszek ED - Scherer, Rafał ED - Korytkowski, Marcin ED - Pedrycz, Witold ED - Tadeusiewicz, Ryszard ED - Zurada, Jacek M TI - Improved Behavioral Analysis of Fuzzy Cognitive Map Models T2 - Artificial Intelligence and Soft Computing PB - Springer Netherlands CY - Cham SN - 9783319912530 T3 - Lecture Notes in Computer Science, ISSN 0302-9743 ; 10842. PY - 2018 SP - 630 EP - 641 PG - 12 DO - 10.1007/978-3-319-91262-2_55 UR - https://m2.mtmt.hu/api/publication/3394825 ID - 3394825 N1 - Megjelent a "Artificial Intelligence and Soft Computing : 17th International Conference, ICAISC 2018 " c. kötetben WoS:hiba:000552709100055 2024-02-19 09:36 típus nem egyezik AB - 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. © Springer International Publishing AG, part of Springer Nature 2018. LA - English DB - MTMT ER - TY - JOUR AU - Hatwágner, F. Miklós AU - Yesil, Engin AU - Dodurka, M. Furkan AU - Papageorgiou, Elpiniki AU - Urbas, Leon AU - Kóczy, T. László TI - Two-Stage Learning Based Fuzzy Cognitive Maps Reduction Approach JF - IEEE TRANSACTIONS ON FUZZY SYSTEMS J2 - IEEE T FUZZY SYST VL - 26 PY - 2018 IS - 5 SP - 2938 EP - 2952 PG - 15 SN - 1063-6706 DO - 10.1109/TFUZZ.2018.2793904 UR - https://m2.mtmt.hu/api/publication/30478603 ID - 30478603 N1 - Department of Information Technology, Széchenyi István University, Gyor, 9026, Hungary Department of Process Control Systems Engineering, Technische Universiẗat Dresden, Dresden, 01069, Germany Getron Corporation, Hoboken, NJ 07030, United States Department of Computer Engineering, Technological Education Institute of Central Greece, Lamia, 35100, Greece Department of Telecommunication and Media Informatics, Budapest University of Technology and Economics, Budapest, 1111, Hungary Cited By :17 Export Date: 7 April 2022 CODEN: IEFSE Correspondence Address: Hatwagner, M.F.; Department of Information Technology, Hungary; email: miklos.hatwagner@sze.hu Funding details: Nemzeti Kutatási Fejlesztési és Innovációs Hivatal, NKFIH, 1687/2015 (IX.25, K108405, K124055 Funding details: Széchenyi István Egyetem, SZE Funding details: National Research, Development and Innovation Office Funding text 1: Manuscript received September 21, 2017; accepted January 8, 2018. Date of publication January 15, 2018; date of current version October 4, 2018. This work was supported in part by the National Research, Development and Innovation Office (NKFIH) under Grant K108405 and Grant K124055, in part by the Individual Government Grant 1687/2015 (IX.25.) to Széchenyi István University, and in part by the UNKP-17-4 New National Excellence Program of the Ministry of Human Resources. (Corresponding author: Miklós Ferenc Hatwágner.) M. F. Hatwágner is with the Department of Information Technology, SzéchenyiIstvánUniversity,Gyo˝r9026, Hungary(e-mail:miklos.hatwagner@ sze.hu). AB - 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. LA - English DB - MTMT ER - TY - JOUR AU - Hegyháti, Máté AU - Ősz, Olivér AU - Hatwágner, F. Miklós TI - A study on solving single stage batch process scheduling problems with an evolutionary algorithm featuring bacterial mutations JF - LECTURE NOTES IN ARTIFICIAL INTELLIGENCE J2 - LECT NOTES ARTIF INT VL - 10841 LNAI PY - 2018 SP - 386 EP - 394 PG - 9 SN - 0302-9743 DO - 10.1007/978-3-319-91253-0_36 UR - https://m2.mtmt.hu/api/publication/27434245 ID - 27434245 N1 - N1 Funding details: EFOP-3.6.1-16-2016-00017, Emberi Eroforrások Minisztériuma N1 Funding text: Acknowledgments. This research was supported by the ÚNKP-17-4 New National Excellence Program of the Ministry of Human Capacities. This research was supported by the EFOP-3.6.1-16-2016-00017; “Internationalization, initiatives to establish a new source of researchers and graduates, and development of knowledge and technological transfer as instruments of intelligent specializations at Szechenyi University” grant. A4 LA - English DB - MTMT ER - TY - JOUR AU - Harmati, István Árpád AU - Hatwágner, F. Miklós AU - Kóczy, T. László TI - On the Existence and Uniqueness of Fixed Points of Fuzzy Cognitive Maps JF - COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE J2 - COMMUN COMPUT INFORM SCI VL - 853 PY - 2018 SP - 490 EP - 500 PG - 11 SN - 1865-0929 DO - 10.1007/978-3-319-91473-2_42 UR - https://m2.mtmt.hu/api/publication/3394816 ID - 3394816 N1 - Megjelent a ".) Information Processing and Management of Uncertainty in Knowledge-Based Systems : Theory and Foundations (17th International Conference, IPMU 2018)" c. kötetben WoS:hiba:000481659500042 2020-08-29 13:00 típus nem egyezik LA - English DB - MTMT ER - TY - CONF AU - Buruzs, Adrienn AU - Kóczy, T. László AU - Hatwágner, F. Miklós ED - Rosana, Rodríguez-López TI - Reduced Model Investigations supported by Fuzzy Cognitive Map to Foster Circular Economy T2 - 9th European Symposium on Computational Intelligence and Mathematics PY - 2017 SP - 165 EP - 175 PG - 11 UR - https://m2.mtmt.hu/api/publication/3280851 ID - 3280851 LA - English DB - MTMT ER - TY - JOUR AU - Elpiniki, I Papageorgiou AU - Hatwágner, F. Miklós AU - Buruzs, Adrienn AU - Kóczy, T. László TI - A concept reduction approach for fuzzy cognitive map models in decision making and management JF - NEUROCOMPUTING J2 - NEUROCOMPUTING VL - 232 PY - 2017 SP - 16 EP - 33 PG - 18 SN - 0925-2312 DO - 10.1016/j.neucom.2016.11.060 UR - https://m2.mtmt.hu/api/publication/3180911 ID - 3180911 LA - English DB - MTMT ER -