A novel RBF training algorithm for short-term electric load forecasting and comparative studies C Cecati, J Kolbusz, P Różycki, P Siano, BM Wilamowski IEEE Transactions on industrial Electronics 62 (10), 6519-6529, 2015 | 258 | 2015 |
Fast and efficient second-order method for training radial basis function networks T Xie, H Yu, J Hewlett, P Rózycki, B Wilamowski IEEE transactions on neural networks and learning systems 23 (4), 609-619, 2012 | 140 | 2012 |
Nonlinear system modeling using RBF networks for industrial application X Meng, P Rozycki, JF Qiao, BM Wilamowski IEEE transactions on industrial informatics 14 (3), 931-940, 2017 | 89 | 2017 |
Recovery of the control plane after failures in ASON/GMPLS networks A Jajszczyk, P Rozycki IEEE network 20 (1), 4-10, 2006 | 53 | 2006 |
A hybrid constructive algorithm for single-layer feedforward networks learning X Wu, P Różycki, BM Wilamowski IEEE Transactions on Neural Networks and Learning Systems 26 (8), 1659-1668, 2014 | 51 | 2014 |
The study of architecture MLP with linear neurons in order to eliminate the “vanishing gradient” problem J Kolbusz, P Rozycki, BM Wilamowski International conference on artificial intelligence and soft computing, 97-106, 2017 | 35 | 2017 |
Failure detection and notification in GMPLS control plane P Rozycki, J Korniak, A Jajszczyk 2007 Workshop on GMPLS Performance: Control Plane Resilience, 1-6, 2007 | 18 | 2007 |
Dedicated deep neural network architectures and methods for their training P Różycki, J Kolbusz, BM Wilamowski 2015 IEEE 19th International Conference on Intelligent Engineering Systems …, 2015 | 13 | 2015 |
GMPLS-simulation tools J Korniak, P Rózycki Proceedings of the 1st Conference Tools of Information Technology, 20-25, 2006 | 11 | 2006 |
Polynet: a polynomial-based learning machine for universal approximation MS Pukish, P Różycki, BM Wilamowski IEEE Transactions on Industrial Informatics 11 (3), 708-716, 2015 | 10 | 2015 |
Using Parity-N Problems as a Way to Compare Abilities of Shallow, Very Shallow and Very Deep Architectures P Różycki, J Kolbusz, T Bartczak, BM Wilamowski International Conference on Artificial Intelligence and Soft Computing, 112-122, 2015 | 8 | 2015 |
Error back propagation algorithm with adaptive learning rate J Kolbusz, P Rozycki, O Lysenko, BM Wilamowski 2019 International Conference on Information and Digital Technologies (IDT …, 2019 | 7 | 2019 |
Estimation of deep neural networks capabilities using polynomial approach P Rozycki, J Kolbusz, R Korostenskyi, BM Wilamowski International Conference on Artificial Intelligence and Soft Computing, 136-147, 2016 | 6 | 2016 |
Signaling improvements for GMPLS control plane J Korniak, P Rozycki Proceedings of the 2nd Conference Tools of the Information Technology, 29-34, 2007 | 6 | 2007 |
Implementation of deep neural networks for industry applications P Rozycki, J Kolbusz, G Krzos, BM Wilamowski IECON 2018-44th Annual Conference of the IEEE Industrial Electronics Society …, 2018 | 5 | 2018 |
Estimation of deep neural networks capabilities based on a trigonometric approach P Rozycki, J Kolbusz, BM Wilamowski 2016 IEEE 20th Jubilee International Conference on Intelligent Engineering …, 2016 | 5 | 2016 |
Spectral image recognition using artificial dynamic neural network in information resonance mode I Peleshchak, R Peleshchak, V Lytvyn, J Kopka, M Wrzesien, J Korniak, ... Artificial Intelligence and Industrial Applications: Smart Operation …, 2021 | 3 | 2021 |
Innowacyjna Gmina. Informatyka w jednostkach samorządu terytorialnego M Hajder Wyższa Szkoła Informatyki i Zarządzania z siedzibą w Rzeszowie, 2014 | 3 | 2014 |
The weighted graphs approach for the GMPLS network reliability enhancement P Rozycki, A Jajszczyk International Congress on Ultra Modern Telecommunications and Control …, 2010 | 3 | 2010 |
Service availability analysis of GMPLS network J Korniak, P Rozycki 2010 14th International Telecommunications Network Strategy and Planning …, 2010 | 3 | 2010 |