標題: Reinforcement Self-Adaptive Evolutionary Algorithm for Fuzzy Systems Design
作者: Hsu, Yung-Chi
Lin, Sheng-Fuu
電控工程研究所
Institute of Electrical and Control Engineering
公開日期: 2008
摘要: This paper proposes a reinforcement self-adaptive evolutionary algorithm (R-SAEA) with fuzzy system for solving control problems. The proposed R-SAEA combines the modified compact genetic algorithm (MCGA) and the modified variable-length genetic algorithm (MVGA) to perform the structure/parameter learning for constructing the fuzzy system dynamically. That is, both the number of rules and the adjustment of parameters in the fuzzy system are designed concurrently by the R-SAEA. The illustrative example was conducted to show the performance and applicability of the proposed R-SAEA method.
URI: http://hdl.handle.net/11536/2697
ISBN: 978-1-4244-1705-6
期刊: 2008 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY, VOLS 1-5
起始頁: 340
結束頁: 345
Appears in Collections:Conferences Paper