標題: Reinforcement group cooperation-based symbiotic evolution for recurrent wavelet-based neuro-fuzzy systems
作者: Hsu, Yung-Chi
Lin, Sheng-Fuu
電控工程研究所
Institute of Electrical and Control Engineering
關鍵字: Neuro-fuzzy system;Symbiotic evolution;Control;Reinforcement learning;Recurrent network
公開日期: 1-Jun-2009
摘要: This paper proposes a recurrent wavelet-based neuro-fuzzy system (RWNFS) with a reinforcement group cooperation-based symbiotic evolution (R-GCSE) for solving various control problems. The R-GCSE is different from the traditional symbiotic evolution. In the R-GCSE method, a population is divided to several groups. Each group formed by a set of chromosomes represents a fuzzy rule and cooperates with other groups to generate better chromosomes by using the proposed elite-based compensation crossover strategy (ECCS). In this paper, the proposed R-GCSE is used to evaluate numerical control problems. The performance of the R-GCSE in the simulations is excellent compared with other existing models. (c) 2009 Elsevier B.V. All rights reserved.
URI: http://dx.doi.org/10.1016/j.neucom.2008.12.027
http://hdl.handle.net/11536/7198
ISSN: 0925-2312
DOI: 10.1016/j.neucom.2008.12.027
期刊: NEUROCOMPUTING
Volume: 72
Issue: 10-12
起始頁: 2418
結束頁: 2432
Appears in Collections:Articles


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