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2020 – today
- 2024
[j80]Abdulrahman K. Eesee
, Szilárd Jaskó, György Eigner, János Abonyi, Tamás Ruppert:
Extension of HAAS for the Management of Cognitive Load. IEEE Access 12: 16559-16572 (2024)- [j79]Ádám Ipkovich, János Abonyi:
Neighborhood Ranking-Based Feature Selection. IEEE Access 12: 20152-20168 (2024) - [j78]Éva Kenyeres, János Abonyi:
Analysis and Clustering-Based Improvement of Particle Filter Optimization Algorithms. IEEE Access 12: 55600-55619 (2024) - [j77]Tamás Kegyes, Zoltán Süle, János Abonyi:
Disassembly line optimization with reinforcement learning. Central Eur. J. Oper. Res. 32(4): 1115-1142 (2024) - [j76]András Rácz-Szabó, Tamás Ruppert, János Abonyi:
Multilayer Network-Based Evaluation of the Efficiency and Resilience of Network Flows. Complex. 2024 (2024) - [j75]Tuan-anh Tran, Tamás Ruppert, János Abonyi:
The Use of eXplainable Artificial Intelligence and Machine Learning Operation Principles to Support the Continuous Development of Machine Learning-Based Solutions in Fault Detection and Identification. Comput. 13(10): 252 (2024) - [j74]Éva Kenyeres, Alex Kummer, János Abonyi:
Machine Learning Classifier-Based Metrics Can Evaluate the Efficiency of Separation Systems. Entropy 26(7): 571 (2024) - [j73]Francesco Pilati, Andrea Sbaragli, Tamás Ruppert, János Abonyi:
Goal-oriented clustering algorithm to monitor the efficiency of logistic processes through real-time locating systems. Int. J. Comput. Integr. Manuf. 37(10-11): 1359-1375 (2024) - [j72]Tamás Kegyes, Alex Kummer, Zoltán Süle, János Abonyi:
Generally Applicable Q-Table Compression Method and Its Application for Constrained Stochastic Graph Traversal Optimization Problems. Inf. 15(4): 193 (2024) - [j71]Róbert Csalódi, Zsolt Bagyura, Ágnes Vathy-Fogarassy, János Abonyi:
Time-dependent frequent sequence mining-based survival analysis. Knowl. Based Syst. 296: 111885 (2024) - [j70]András Darányi, János Abonyi:
Fault Diagnostics Based on the Analysis of Probability Distributions Estimated Using a Particle Filter. Sensors 24(3): 719 (2024) - [j69]Tímea Czvetkó, János Abonyi:
Version [1.0]- HAT-VIS - A MATLAB-based hypergraph visualization tool. SoftwareX 28: 101963 (2024) - [c29]Mónika Gugolya, Tibor Medvegy, János Abonyi, Tamás Ruppert:
Game-Based Design of a Human-Machine Collaboration Monitoring System. APMS (2) 2024: 205-219 - [c28]Zoltán Jeskó, Tuan-anh Tran, Gergely Halász, János Abonyi, Tamás Ruppert:
Enriching Scene-Graph Generation with Prior Knowledge from Work Instruction. APMS (2) 2024: 290-302 - 2023
- [j68]Yuli Sudriani, Viktor Sebestyén, János Abonyi:
Surface Water Monitoring Systems - The Importance of Integrating Information Sources for Sustainable Watershed Management. IEEE Access 11: 36421-36451 (2023) - [j67]László Bántay, János Abonyi:
Frequent pattern mining-based log file partition for process mining. Eng. Appl. Artif. Intell. 123(Part A): 106221 (2023) - [j66]Tímea Czvetkó, János Abonyi:
Data sharing in Industry 4.0 - AutomationML, B2MML and International Data Spaces-based solutions. J. Ind. Inf. Integr. 33: 100438 (2023) - [j65]Tamás Ruppert, András Darányi, Tibor Medvegy, Dániel Csereklei, János Abonyi:
Demonstration Laboratory of Industry 4.0 Retrofitting and Operator 4.0 Solutions: Education towards Industry 5.0. Sensors 23(1): 283 (2023) - [j64]János Hegedüs-Kuti, József Szolosi, Dániel Varga, János Abonyi, Mátyás Andó, Tamás Ruppert:
3D Scanner-Based Identification of Welding Defects - Clustering the Results of Point Cloud Alignment. Sensors 23(5): 2503 (2023) - [j63]Tuan-anh Tran, Márta Péntek, Hossein Motahari-Nezhad, János Abonyi, Levente Kovács, László Gulácsi, György Eigner, Zsombor Zrubka, Tamás Ruppert:
Heart Rate Variability Measurement to Assess Acute Work-Content-Related Stress of Workers in Industrial Manufacturing Environment - A Systematic Scoping Review. IEEE Trans. Syst. Man Cybern. Syst. 53(11): 6685-6692 (2023) - [c27]László Nagy, Tamás Ruppert, János Abonyi:
Towards an Ontology-Based Fault Detection and Diagnosis Framework - A Semantic Approach. CoDIT 2023: 1267-1272 - [c26]Gergely Halász, Tibor Medvegy, János Abonyi, Tamás Ruppert:
Indoor Positioning-based Occupational Exposures Mapping and Operator Well-being Assessment in Manufacturing Environment. APMS (1) 2023: 543-555 - 2022
- [j62]Tuan-anh Tran, Tamás Ruppert, György Eigner, János Abonyi:
Retrofitting-Based Development of Brownfield Industry 4.0 and Industry 5.0 Solutions. IEEE Access 10: 64348-64374 (2022) - [j61]Krisztián Bakon, Tibor Holczinger, Zoltán Süle, Szilárd Jaskó, János Abonyi:
Scheduling Under Uncertainty for Industry 4.0 and 5.0. IEEE Access 10: 74977-75017 (2022) - [j60]Laszlo Gadar, Zsolt Tibor Kosztyán, András Telcs, János Abonyi:
Cooperation patterns in the ERASMUS student exchange network: an empirical study. Appl. Netw. Sci. 7(1): 74 (2022) - [j59]Ádám Sass, Alex Kummer, János Abonyi:
Multi-agent reinforcement learning-based exploration of optimal operation strategies of semi-batch reactors. Comput. Chem. Eng. 162: 107819 (2022) - [j58]László Bántay, Gyula Dörgö, Ferenc Tandari, János Abonyi:
Simultaneous Process Mining of Process Events and Operator Actions for Alarm Management. Complex. 2022: 8670154:1-8670154:13 (2022) - [j57]Zsolt Tibor Kosztyán, András Telcs, János Abonyi:
A multi-block clustering algorithm for high dimensional binarized sparse data. Expert Syst. Appl. 191: 116219 (2022) - [j56]Beáta Sz. G. Pató, Klaudia Kovacs, János Abonyi:
Challenges of the Fourth Industrial Revolution in HRM. Int. J. Hum. Cap. Inf. Technol. Prof. 13(1): 1-14 (2022) - [j55]Lalit Maurya, Viney Lohchab, Prasant Kumar Mahapatra, János Abonyi:
Contrast and brightness balance in image enhancement using Cuckoo Search-optimized image fusion. J. King Saud Univ. Comput. Inf. Sci. 34(9): 7247-7258 (2022) - [j54]Pál Péter Hanzelik, Alex Kummer, János Abonyi:
Edge-Computing and Machine-Learning-Based Framework for Software Sensor Development. Sensors 22(11): 4268 (2022) - [c25]László Nagy, Tamás Ruppert, János Abonyi:
Human-centered knowledge graph-based design concept for collaborative manufacturing. ETFA 2022: 1-8 - [c24]Tamás Ruppert, Andreas Löcklin, David Romero, János Abonyi:
Intelligent Collaborative Manufacturing Space for Augmenting Human Workers in Semi-Automated Manufacturing Systems. ETFA 2022: 1-7 - [c23]Tuan-anh Tran, János Abonyi, Levente Kovács, György Eigner, Tamás Ruppert:
Heart Rate Variability Measurement to Assess Work-Related Stress of Physical Workers in Manufacturing Industries - Protocol for a Systematic Literature Review. SISY 2022: 313-318 - 2021
- [j53]Róbert Csalódi, Zsolt Bagyura, János Abonyi:
Mixture of Survival Analysis Models-Cluster-Weighted Weibull Distributions. IEEE Access 9: 152288-152299 (2021) - [j52]Tamás Ruppert, Róbert Csalódi, János Abonyi:
Estimation of machine setup and changeover times by survival analysis. Comput. Ind. Eng. 153: 107026 (2021) - [j51]Róbert Csalódi, Zoltán Süle, Szilárd Jaskó, Tibor Holczinger, János Abonyi:
Industry 4.0-Driven Development of Optimization Algorithms: A Systematic Overview. Complex. 2021: 6621235:1-6621235:22 (2021) - [j50]Tamás Kegyes, Zoltán Süle, János Abonyi:
The Applicability of Reinforcement Learning Methods in the Development of Industry 4.0 Applications. Complex. 2021: 7179374:1-7179374:31 (2021) - [j49]János Abonyi, Richard Karoly, Gyula Dörgö:
Event-Tree Based Sequence Mining Using LSTM Deep-Learning Model. Complex. 2021: 7887159:1-7887159:24 (2021) - [j48]László Nagy, Tamás Ruppert, János Abonyi:
Ontology-Based Analysis of Manufacturing Processes: Lessons Learned from the Case Study of Wire Harness Production. Complex. 2021: 8603515:1-8603515:21 (2021) - [j47]Róbert Csalódi, Zoltán Birkner, János Abonyi:
Learning Interpretable Mixture of Weibull Distributions - Exploratory Analysis of How Economic Development Influences the Incidence of COVID-19 Deaths. Data 6(12): 125 (2021) - [j46]Laszlo Heinold, Ágnes Bárkányi, János Abonyi:
Test Plan for the Verification of the Robustness of Sensors and Automotive Electronic Products Using Scenario-Based Noise Deployment (SND). Sensors 21(10): 3359 (2021) - [c22]Tuan-anh Tran, Tamás Ruppert, György Eigner, János Abonyi:
Real-time locating system and digital twin in Lean 4.0. SACI 2021: 369-374 - 2020
- [b3]Dániel Leitold, Ágnes Vathy-Fogarassy, János Abonyi:
Network-Based Analysis of Dynamical Systems - Methods for Controllability and Observability Analysis, and Optimal Sensor Placement. Springer Briefs in Computer Science, Springer 2020, ISBN 978-3-030-36471-7, pp. 1-85 - [j45]Szilárd Jaskó, Adrienn Skrop, Tibor Holczinger, Tibor Chován, János Abonyi:
Development of manufacturing execution systems in accordance with Industry 4.0 requirements: A review of standard- and ontology-based methodologies and tools. Comput. Ind. 123: 103300 (2020) - [j44]Tamás Ruppert, János Abonyi:
Integration of real-time locating systems into digital twins. J. Ind. Inf. Integr. 20: 100174 (2020) - [j43]András Rácz-Szabó, Tamás Ruppert, László Bántay, Andreas Löcklin, László Jakab, János Abonyi:
Real-Time Locating System in Production Management. Sensors 20(23): 6766 (2020)
2010 – 2019
- 2019
- [j42]Gyula Dörgö, János Abonyi:
Learning and predicting operation strategies by sequence mining and deep learning. Comput. Chem. Eng. 128: 174-187 (2019) - [j41]Alex Kummer, Tamás Varga, János Abonyi:
Genetic programming-based development of thermal runaway criteria. Comput. Chem. Eng. 131 (2019) - [j40]János Baumgartner, Zoltán Süle, Botond Bertók, János Abonyi:
Test-sequence optimisation by survival analysis. Central Eur. J. Oper. Res. 27(2): 357-375 (2019) - [j39]Daniel Leitold, Ágnes Vathy-Fogarassy, János Abonyi:
Empirical working time distribution-based line balancing with integrated simulated annealing and dynamic programming. Central Eur. J. Oper. Res. 27(2): 455-473 (2019) - [j38]Gergely Marcell Honti, János Abonyi:
A Review of Semantic Sensor Technologies in Internet of Things Architectures. Complex. 2019: 6473160:1-6473160:21 (2019) - [i2]Dániel Leitold, Ágnes Vathy-Fogarassy, János Abonyi:
Network-based Observability and Controllability Analysis of Dynamical Systems: the NOCAD toolbox. F1000Research 8: 646 (2019) - 2018
- [j37]Gyula Dörgö, János Abonyi:
Sequence Mining Based Alarm Suppression. IEEE Access 6: 15365-15379 (2018) - [j36]Gyula Dörgö, Kristof Varga, János Abonyi:
Hierarchical Frequent Sequence Mining Algorithm for the Analysis of Alarm Cascades in Chemical Processes. IEEE Access 6: 50197-50216 (2018) - [j35]Laszlo Gadar, Zsolt Tibor Kosztyán, János Abonyi:
The Settlement Structure Is Reflected in Personal Investments: Distance-Dependent Network Modularity-Based Measurement of Regional Attractiveness. Complex. 2018: 1306704:1-1306704:16 (2018) - [j34]Tamás Ruppert, Gergely Marcell Honti, János Abonyi:
Multilayer Network-Based Production Flow Analysis. Complex. 2018: 6203754:1-6203754:15 (2018) - [j33]Tamás Ruppert, János Abonyi:
Software Sensor for Activity-Time Monitoring and Fault Detection in Production Lines. Sensors 18(7): 2346 (2018) - [j32]Daniel Leitold, Ágnes Vathy-Fogarassy, János Abonyi:
Network Distance-Based Simulated Annealing and Fuzzy Clustering for Sensor Placement Ensuring Observability and Minimal Relative Degree. Sensors 18(9): 3096 (2018) - 2016
- [j31]András Király, Ágnes Vathy-Fogarassy, János Abonyi:
Geodesic distance based fuzzy c-medoid clustering - searching for central points in graphs and high dimensional data. Fuzzy Sets Syst. 286: 157-172 (2016) - [c21]Richard Karoly, János Abonyi:
Multi-temporal sequential pattern mining based improvement of alarm management systems. SMC 2016: 3870-3875 - [p3]Tibor Kulcsar, Barbara Farsang, Sándor Zoltán Németh, János Abonyi:
Multivariate Statistical and Computational Intelligence Techniques for Quality Monitoring of Production Systems. Intelligent Decision Making in Quality Management 2016: 237-263 - 2015
- [b2]Tamás Kenesei, János Abonyi:
Interpretability of Computational Intelligence-Based Regression Models. Springer Briefs in Computer Science, Springer 2015, ISBN 978-3-319-21941-7, pp. 1-63 - [j30]András Király, János Abonyi:
Redesign of the supply of mobile mechanics based on a novel genetic optimization algorithm using Google Maps API. Eng. Appl. Artif. Intell. 38: 122-130 (2015) - [j29]Zoltán Bankó, János Abonyi:
Mixed dissimilarity measure for piecewise linear approximation based time series applications. Expert Syst. Appl. 42(21): 7664-7675 (2015) - 2014
- [j28]András Király, Asta Laiho, János Abonyi, Attila Gyenesei:
Novel techniques and an efficient algorithm for closed pattern mining. Expert Syst. Appl. 41(11): 5105-5114 (2014) - [c20]András Király, Ágnes Vathy-Fogarassy, János Abonyi:
Fuzzy c-Medoid Graph Clustering. ICAISC (2) 2014: 738-748 - [i1]Tamás Varga, András Király, János Abonyi:
Improvement of PSO algorithm by memory based gradient search - application in inventory management. CoRR abs/1410.5652 (2014) - 2013
- [b1]Ágnes Vathy-Fogarassy, János Abonyi:
Graph-Based Clustering and Data Visualization Algorithms. Springer Briefs in Computer Science, Springer 2013, ISBN 978-1-4471-5157-9, pp. I-XIII, 1-110 - [j27]Tamás Kenesei, János Abonyi:
Hinging hyperplane based regression tree identified by fuzzy clustering and its application. Appl. Soft Comput. 13(2): 782-792 (2013) - 2012
- [j26]Tamás Kenesei, János Abonyi:
Interpretable support vector regression. Artif. Intell. Res. 1(2): 11-21 (2012) - [j25]Zoltán Bankó, János Abonyi:
Correlation based dynamic time warping of multivariate time series. Expert Syst. Appl. 39(17): 12814-12823 (2012) - [c19]András Király, János Abonyi, Asta Laiho, Attila Gyenesei:
Biclustering of High-throughput Gene Expression Data with Bicluster Miner. ICDM Workshops 2012: 131-138 - 2011
- [p2]András Király, János Abonyi:
Optimization of Multiple Traveling Salesmen Problem by a Novel Representation Based Genetic Algorithm. Intelligent Computational Optimization in Engineering 2011: 241-269
2000 – 2009
- 2009
- [j24]Tamás Varga, Ferenc Szeifert, János Abonyi:
Decision tree and first-principles model-based approach for reactor runaway analysis and forecasting. Eng. Appl. Artif. Intell. 22(4-5): 569-578 (2009) - [j23]Ágnes Vathy-Fogarassy, János Abonyi:
Local and global mappings of topology representing networks. Inf. Sci. 179(21): 3791-3803 (2009) - [c18]Balazs Balaskó, Sándor Zoltán Németh, János Abonyi:
Integrated process and control system model for product quality control - A soft-sensor based application. ECC 2009: 3498-3502 - [c17]János Abonyi:
Supervised Fuzzy Clustering Based Initialization of Fuzzy Partitions for Decision Tree Induction. WSC 2009: 31-39 - [c16]Zoltán Bankó, János Abonyi:
Dynamic Time Warping of Segmented Time Series. WSC 2009: 117-125 - 2008
- [j22]Ferenc Peter Pach, Attila Gyenesei, János Abonyi:
Compact fuzzy association rule-based classifier. Expert Syst. Appl. 34(4): 2406-2416 (2008) - [j21]Ferenc Peter Pach, Attila Gyenesei, János Abonyi:
MOSSFARM: Model structure selection by fuzzy association rule mining. J. Intell. Fuzzy Syst. 19(6): 399-407 (2008) - [j20]Ágnes Vathy-Fogarassy, Agnes Werner-Stark, János Abonyi:
Topology Representing Networks for the Visualization of Manifolds. J. Math. Model. Algorithms 7(4): 351-370 (2008) - [j19]Ágnes Vathy-Fogarassy, Attila Kiss, János Abonyi:
Topology Representing Network Map - A New Tool for Visualization of High-Dimensional Data. Trans. Comput. Sci. 1: 61-84 (2008) - [p1]Balazs Feil, János Abonyi:
Introduction to Fuzzy Data Mining Methods. Handbook of Research on Fuzzy Information Processing in Databases 2008: 55-95 - 2007
- [j18]Balazs Feil, Balazs Balasko, János Abonyi:
Visualization of fuzzy clusters by fuzzy Sammon mapping projection: application to the analysis of phase space trajectories. Soft Comput. 11(5): 479-488 (2007) - [c15]Tamás Kenesei, Johannes A. Roubos, János Abonyi:
A Combination-of-Tools Method for Learning Interpretable Fuzzy Rule-Based Classifiers from Support Vector Machines. IDEAL 2007: 477-486 - [c14]Ágnes Vathy-Fogarassy, Agnes Werner-Stark, Balázs Gaál, János Abonyi:
Visualization of Topology Representing Networks. IDEAL 2007: 557-566 - [c13]Tamás Kenesei, Balazs Feil, János Abonyi:
Fuzzy Clustering for the Identification of Hinging Hyperplanes Based Regression Trees. WILF 2007: 179-186 - [c12]Ágnes Vathy-Fogarassy, Attila Kiss, János Abonyi:
Improvement of Jarvis-Patrick Clustering Based on Fuzzy Similarity. WILF 2007: 195-202 - 2006
- [j17]Peter Pach, Balazs Feil, Sándor Zoltán Németh, Peter Arva, János Abonyi:
Process-Data-Warehousing-Based Operator Support System for Complex Production Technologies. IEEE Trans. Syst. Man Cybern. Part A 36(1): 136-153 (2006) - [c11]Ágnes Vathy-Fogarassy, Attila Kiss, János Abonyi:
Hybrid Minimal Spanning Tree and Mixture of Gaussians Based Clustering Algorithm. FoIKS 2006: 313-330 - [c10]Balazs Balasko, János Madár, János Abonyi:
Additive Sequential Evolutionary Design of Experiments. ICAISC 2006: 324-333 - 2005
- [j16]Balazs Feil, János Abonyi, Sándor Zoltán Németh, Peter Arva:
Monitoring process transitions by Kalman filtering and time-series segmentation. Comput. Chem. Eng. 29(6): 1423-1431 (2005) - [j15]János Madár, János Abonyi, Ferenc Szeifert:
Interactive evolutionary computation in process engineering. Comput. Chem. Eng. 29(7): 1591-1597 (2005) - [j14]János Madár, János Abonyi, Ferenc Szeifert:
Feedback linearizing control using hybrid neural networks identified by sensitivity approach. Eng. Appl. Artif. Intell. 18(3): 343-351 (2005) - [j13]János Abonyi, Balazs Feil, Sándor Zoltán Németh, Peter Arva:
Modified Gath-Geva clustering for fuzzy segmentation of multivariate time-series. Fuzzy Sets Syst. 149(1): 39-56 (2005) - [j12]János Abonyi, Balazs Feil, Ajith Abraham:
Computational Intelligence in Data Mining. Informatica (Slovenia) 29(1): 3-12 (2005) - [c9]János Madár, János Abonyi, Ferenc Szeifert:
Interactive Particle Swarm Optimization. ISDA 2005: 314-319 - 2004
- [j11]János Madár, Ferenc Szeifert, Lajos Nagy, Tibor Chován, János Abonyi:
Tendency model-based improvement of the slave loop in cascade temperature control of batch process units. Comput. Chem. Eng. 28(5): 737-744 (2004) - [j10]Stanimir Mollov, Robert Babuska, János Abonyi, Henk B. Verbruggen:
Effective optimization for fuzzy model predictive control. IEEE Trans. Fuzzy Syst. 12(5): 661-675 (2004) - [c8]János Abonyi, Robert Babuska:
FUZZSAM - visualization of fuzzy clustering results by modified Sammon mapping. FUZZ-IEEE 2004: 365-370 - [c7]Daniela Girimonte, Robert Babuska, János Abonyi:
Fuzzy clustering for selecting structure of nonlinear models with mixed discrete and continuous inputs. FUZZ-IEEE 2004: 383-387 - [c6]Balazs Feil, János Abonyi, Peter Pach, Sándor Zoltán Németh, Peter Arva, Miklos Nemeth, Gabor Nagy:
Semi-mechanistic Models for State-Estimation - Soft Sensor for Polymer Melt Index Prediction. ICAISC 2004: 1111-1117 - [c5]János Abonyi, Balazs Feil, Sándor Zoltán Németh, Peter Arva, Robert Babuska:
State-space reconstruction and prediction of chaotic time series based on fuzzy clustering. SMC (3) 2004: 2374-2380 - 2003
- [j9]János Abonyi, Sándor Zoltán Németh, Csaba Vincze, Peter Arva:
Process analysis and product quality estimation by Self-Organizing Maps with an application to polyethylene production. Comput. Ind. 52(3): 221-234 (2003) - [j8]János Abonyi, Johannes A. Roubos, Ferenc Szeifert:
Data-driven generation of compact, accurate, and linguistically sound fuzzy classifiers based on a decision-tree initialization. Int. J. Approx. Reason. 32(1): 1-21 (2003) - [j7]Johannes A. Roubos, Magne Setnes, János Abonyi:
Learning fuzzy classification rules from labeled data. Inf. Sci. 150(1-2): 77-93 (2003) - [j6]János Abonyi, Ferenc Szeifert:
Supervised fuzzy clustering for the identification of fuzzy classifiers. Pattern Recognit. Lett. 24(14): 2195-2207 (2003) - [c4]János Abonyi, Robert Babugkao, Balazs Feil:
Structure selection for nonlinear input-output models based on fuzzy cluster analysis. FUZZ-IEEE 2003: 464-469 - [c3]János Abonyi, Balazs Feil, Sándor Zoltán Németh, Peter Arva:
Fuzzy Clustering Based Segmentation of Time-Series. IDA 2003: 275-285 - 2002
- [j5]János Abonyi, Robert Babuska, Ferenc Szeifert:
Modified Gath-Geva fuzzy clustering for identification of Takagi-Sugeno fuzzy models. IEEE Trans. Syst. Man Cybern. Part B 32(5): 612-621 (2002) - 2001
- [j4]János Abonyi, Lajos Nagy, Ferenc Szeifert:
Fuzzy model-based predictive control by instantaneous linearization. Fuzzy Sets Syst. 120(1): 109-122 (2001) - [j3]János Abonyi, Robert Babuska, Ferenc Szeifert:
Fuzzy modeling with multivariate membership functions: gray-box identification and control design. IEEE Trans. Syst. Man Cybern. Part B 31(5): 755-767 (2001) - [c2]János Abonyi, Johannes A. Roubos, Marcel Oosterom, Ferenc Szeifert:
Compact TS - Fuzzy Models Through Clustering and OLS Plus FIS Model Reduction. FUZZ-IEEE 2001: 1420-1423 - 2000
- [j2]János Abonyi, Lajos Nagy, Ferenc Szeifert:
Hybrid fuzzy convolution modelling and identification of chemical process systems. Int. J. Syst. Sci. 31(4): 457-466 (2000) - [j1]János Abonyi, Robert Babuska, Henk B. Verbruggen, Ferenc Szeifert:
Incorporating prior knowledge in fuzzy model identification. Int. J. Syst. Sci. 31(5): 657-667 (2000) - [c1]János Abonyi, Robert Babuska:
Local and global identification and interpretation of parameters in Takagi-Sugeno fuzzy models. FUZZ-IEEE 2000: 835-840
Coauthor Index
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