Novel on-line speed profile generation for industrial machine tool based on flexible neuro-fuzzy approximation KC Leszek Rutkowski, Andrzej Przybył IEEE Transactions on Industrial Electronics 59 (2), 1238-1247, 2012 | 101* | 2012 |
A new method for designing neuro-fuzzy systems for nonlinear modelling with interpretability aspects K Cpałka, K Łapa, A Przybył, M Zalasiński Neurocomputing 135, 203-217, 2014 | 86 | 2014 |
Online speed profile generation for industrial machine tool based on neuro-fuzzy approach L Rutkowski, A Przybył, K Cpałka, MJ Er International Conference on Artificial Intelligence and Soft Computing, 645-650, 2010 | 56 | 2010 |
A new approach to nonlinear modelling of dynamic systems based on fuzzy rules Ł Bartczuk, A Przybył, K Cpałka International Journal of Applied Mathematics and Computer Science 26 (3), 2016 | 53 | 2016 |
A new approach to designing interpretable models of dynamic systems K Łapa, A Przybył, K Cpałka International Conference on Artificial Intelligence and Soft Computing, 523-534, 2013 | 47 | 2013 |
Some aspects of evolutionary designing optimal controllers J Szczypta, A Przybył, K Cpałka International Conference on Artificial Intelligence and Soft Computing, 91-100, 2013 | 46 | 2013 |
A new approach to design of control systems using genetic programming K Cpalka, K Łapa, A Przybył Information technology and control 44 (4), 433-442, 2015 | 45 | 2015 |
A new method to construct of interpretable models of dynamic systems A Przybył, K Cpałka International Conference on Artificial Intelligence and Soft Computing, 697-705, 2012 | 43 | 2012 |
A new algorithm for identification of significant operating points using swarm intelligence P Dziwiński, Ł Bartczuk, A Przybył, ED Avedyan Artificial Intelligence and Soft Computing: 13th International Conference …, 2014 | 33 | 2014 |
New method for nonlinear fuzzy correction modelling of dynamic objects Ł Bartczuk, A Przybył, P Koprinkova-Hristova Artificial Intelligence and Soft Computing: 13th International Conference …, 2014 | 27 | 2014 |
Genetic programming algorithm for designing of control systems K Cpalka, K Łapa, A Przybył Information Technology and Control 47 (4), 668-683, 2018 | 21 | 2018 |
Genetic Algorithm for Observer Parameters Tuning in Sensorless Induction Motor Drive. AP Jerzy Jelonkiewicz Neural Networks and Soft Computing. Proceedings of the Sixth International …, 2003 | 21* | 2003 |
HARDWARE IMPLEMENTATION OF A TAKAGI-SUGENO NEURO-FUZZY SYSTEM OPTIMIZED BY A POPULATION ALGORITHM P Dziwinski, A Przybył, P Trippner, J Paszkowski, Y Hayashi Journal of Artificial Intelligence and Soft Computing Research 11 (3), 243 - 266, 2021 | 19 | 2021 |
Hybrid state variables-fuzzy logic modelling of nonlinear objects Ł Bartczuk, A Przybył, P Dziwiński Artificial Intelligence and Soft Computing: 12th International Conference …, 2013 | 19 | 2013 |
Distributed control system based on real time ethernet for computer numerical controlled machine tool A Przybyl, J Smolag, P Kimla Przeglad Elektrotechniczny 86 (2), 342-346, 2010 | 17 | 2010 |
The method of hardware implementation of fuzzy systems on FPGA A Przybył, MJ Er Artificial Intelligence and Soft Computing: 15th International Conference …, 2016 | 13 | 2016 |
The idea for the integration of neuro-fuzzy hardware emulators with real-time network A Przybył, MJ Er International Conference on Artificial Intelligence and Soft Computing, 279-294, 2014 | 12 | 2014 |
Evolutionary approach with multiple quality criteria for controller design J Szczypta, A Przybył, L Wang Artificial Intelligence and Soft Computing: 13th International Conference …, 2014 | 12 | 2014 |
Fixed-point arithmetic unit with a scaling mechanism for FPGA-based embedded systems A Przybył Electronics 10 (10), 1164, 2021 | 11 | 2021 |
Negative space-based population initialization algorithm (NSPIA) K Łapa, K Cpałka, A Przybył, K Grzanek Artificial Intelligence and Soft Computing: 17th International Conference …, 2018 | 11 | 2018 |