A multi-objective genetic optimization for fast, fuzzy rule-based credit classification with balanced accuracy and interpretability MB Gorzałczany, F Rudziński Applied Soft Computing 40, 206-220, 2016 | 145 | 2016 |
A multi-objective genetic optimization of interpretability-oriented fuzzy rule-based classifiers F Rudziński Applied Soft Computing 38, 118-133, 2016 | 101 | 2016 |
Interpretable and accurate medical data classification–a multi-objective genetic-fuzzy optimization approach MB Gorzałczany, F Rudziński Expert Systems with Applications 71, 26-39, 2017 | 81 | 2017 |
Accuracy vs. interpretability of fuzzy rule-based classifiers: an evolutionary approach MB Gorzałczany, F Rudziński International Symposium on Evolutionary Computation, 222-230, 2012 | 37 | 2012 |
A modified Pittsburg approach to design a genetic fuzzy rule-based classifier from data MB Gorzałczany, F Rudziński Artificial Intelligence and Soft Computing: 10th International Conference …, 2010 | 28 | 2010 |
Generalized self-organizing maps for automatic determination of the number of clusters and their multiprototypes in cluster analysis MB Gorzałczany, F Rudziński IEEE Transactions on Neural Networks and Learning Systems 29 (7), 2833-2845, 2017 | 27 | 2017 |
Finding Sets of Non-Dominated Solutions with High Spread and Well-Balanced Distribution using Generalized Strength Pareto Evolutionary Algorithm. F Rudziński 16th World Congress of the International-Fuzzy-Systems-Association (IFSA …, 2015 | 25 | 2015 |
Application of genetic algorithms and Kohonen networks to cluster analysis MB Gorzałczany, F Rudziński International Conference on Artificial Intelligence and Soft Computing, 556-561, 2004 | 22 | 2004 |
Handling fuzzy systems’ accuracy-interpretability trade-off by means of multi-objective evolutionary optimization methods–selected problems MB Gorzałczany, F Rudziński Bulletin of the Polish Academy of Sciences: Technical Sciences, 2015 | 19 | 2015 |
Cluster analysis via dynamic self-organizing neural networks MB Gorzałczany, F Rudziński International Conference on Artificial Intelligence and Soft Computing, 593-602, 2006 | 18 | 2006 |
A modern data-mining approach based on genetically optimized fuzzy systems for interpretable and accurate smart-grid stability prediction MB Gorzałczany, J Piekoszewski, F Rudziński Energies 13 (10), 2559, 2020 | 17 | 2020 |
Modified Kohonen networks for complex cluster-analysis problems MB Gorzałczany, F Rudziński International Conference on Artificial Intelligence and Soft Computing, 562-567, 2004 | 17 | 2004 |
Genetic fuzzy rule-based modelling of dynamic systems using time series MB Gorzałczany, F Rudziński International Symposium on Evolutionary Computation, 231-239, 2012 | 16 | 2012 |
An improved multi-objective evolutionary optimization of data-mining-based fuzzy decision support systems MB Gorzałczany, F Rudziński 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2227-2234, 2016 | 15 | 2016 |
Generalized tree-like self-organizing neural networks with dynamically defined neighborhood for cluster analysis MB Gorzałczany, J Piekoszewski, F Rudziński Artificial Intelligence and Soft Computing: 13th International Conference …, 2014 | 15 | 2014 |
A multi-objective-genetic-optimization-based data-driven fuzzy classifier for technical applications MB Gorzałczany, F Rudziński 2016 IEEE 25th International Symposium on Industrial Electronics (ISIE), 78-83, 2016 | 14 | 2016 |
WWW-newsgroup-document clustering by means of dynamic self-organizing neural networks MB Gorzałczany, F Rudziński International Conference on Artificial Intelligence and Soft Computing, 40-51, 2008 | 12 | 2008 |
Intrusion Detection in Internet of Things With MQTT Protocol—An Accurate and Interpretable Genetic-Fuzzy Rule-Based Solution MB Gorzałczany, F Rudziński IEEE Internet of Things Journal 9 (24), 24843-24855, 2022 | 11 | 2022 |
Business Intelligence in airline passenger satisfaction study—A fuzzy-genetic approach with optimized interpretability-accuracy trade-off MB Gorzałczany, F Rudziński, J Piekoszewski Applied Sciences 11 (11), 5098, 2021 | 9 | 2021 |
Gene expression data clustering using tree-like SOMs with evolving splitting-merging structures MB Gorzałczany, F Rudzínski, J Piekoszewski 2016 International Joint Conference on Neural Networks (IJCNN), 3666-3673, 2016 | 8 | 2016 |