MATEC Web Conf.
Volume 351, 202120th International Conference Diagnostics of Machines and Vehicles “Hybrid Multimedia Mobile Stage”
|Number of page(s)||10|
|Section||Selected Diagnostic Problems of Hybrid Multimedia Mobile Stages|
|Published online||06 December 2021|
- O. Cordon, Genetic fuzzy systems: evolutionary tuning and learning of fuzzy knowledge bases (World Scientific, 2001) [Google Scholar]
- F. Herrera, M. Lozano, J.L. Verdegay, Generating fuzzy rules from examples using genetic algorithms, Fuzzy Logic and Soft Computing, pp. 11-20 (1995) [Google Scholar]
- F. Herrera, M. Lozano, J.L. Verdegay, A learning process for fuzzy control rules using genetic algorithms, Fuzzy Set Syst, Vol. 100 Issue 1-3, pp. 143-158 (1998) [Google Scholar]
- O. Cordon, F. Herrera, L. Sanchez, Evolutionary Learning Processes for Data Analysis in Electrical Engineering Applications (John Wiley & Sons Ltd. 1997) [Google Scholar]
- O. Cordon, M.J. del Jesus, F. Herrera, M. Lozano, MOGUL: A methodology to obtain genetic fuzzy rule‐based systems under the iterative rule learning approach, Int J Intell Syst, Vol. 14 Issue 11, pp. 1123-1153 (1999) [Google Scholar]
- A. Gonzblez, P. Raúl, SLAVE: A genetic learning system based on an iterative approach, IEEE T Fuzzy Syst, Vol. 7 Issue 2, pp. 176-191 (1999). [Google Scholar]
- O. Cordon, F. Herrera, Hybridizing genetic algorithms with sharing scheme and evolution strategies for designing approximate fuzzy rule-based systems, Fuzzy Set Syst, Vol. 118 Issue 2, pp. 235-255 (2001) [Google Scholar]
- M. Pająk, Fuzzy modelling of temperature difference in 200 MW power unit condenser using genetic fuzzy systems, Control Cybern, Vol. 37 Issue 3, pp. 565-583 (2008) [Google Scholar]
- M. Pająk, Genetic Fuzzy system of power units maintenance schedules generation, Journal of Intelligent and Fuzzy Systems, Vol. 28 Issue 4, pp. 1577-1589 (2015) [Google Scholar]
- T. Bäck, Evolutionary Algorithms in Theory and Practice: Evolution Strategies, Evolutionary Programming, Genetic Algorithms (Oxford Scholarship Online, 2020) [Google Scholar]
- Padmavathi Kora, Priyanka Yadlapalli, Crossover Operators in Genetic Algorithms: A Review, Int J Comput Appl, Vol. 162 Issue 10, pp. 34-36 (2017) [Google Scholar]
- A. González, F. Herrera, Multi-stage genetic fuzzy systems based on the iterative rule learning approach, Mathware & Soft Computing, Vol. 4 Issue 3, pp. 233-249 (1997) [Google Scholar]
- Ł. Muślewski, M. Pająk, B. Landowski, B. Żółtowski, A method for determining the usability potential of ship steam boilers, Pol Marit Res, Vol. 92 Issue 4, pp. 105-112 (2016) [Google Scholar]
- M. Pająk, Identification of the operating parameters of a complex technical system important from the operational potential point of view, P I Mech Eng I-J Sys, Vol. 232 Issue 1, pp. 62-78 (2018) [Google Scholar]
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