Reinforcement self-adaptive evolutionary algorithm for fuzzy systems design

Yung C. Hsu*, Sheng-Fuu Lin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Industrial Technology, IEEE ICIT 2008 - Conference Proceedings
DOIs
StatePublished - 30 Oct 2008
Event2008 IEEE International Conference on Industrial Technology, IEEE ICIT 2008 - Chengdu, China
Duration: 21 Apr 200824 Apr 2008

Publication series

NameProceedings of the IEEE International Conference on Industrial Technology

Conference

Conference2008 IEEE International Conference on Industrial Technology, IEEE ICIT 2008
CountryChina
CityChengdu
Period21/04/0824/04/08

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