標題: Multi groups cooperation based symbiotic evolution for TSK-type neuro-fuzzy systems design
作者: Hsu, Yung-Chi
Lin, Sheng-Fuu
Cheng, Yi-Chang
電控工程研究所
Institute of Electrical and Control Engineering
關鍵字: Genetic algorithms;Symbiotic evolution;Chaotic time series;Neural fuzzy system
公開日期: 1-七月-2010
摘要: In this paper, a TSK-type neuro-fuzzy system with multi groups cooperation based symbiotic evolution method (TNFS-MGCSE) is proposed. The TNFS-MGCSE is developed from symbiotic evolution. The symbiotic evolution is different from traditional GAs (genetic algorithms) that each chromosome in symbiotic evolution represents a rule of fuzzy model. The MGCSE is different from the traditional symbiotic evolution; with a population in MGCSE is divided into several groups. Each group formed by a set of chromosomes represents a fuzzy rule and cooperate with other groups to generate the better chromosomes by using the proposed cooperation based crossover strategy (CCS). In this paper, the proposed TNFS-MGCSE is used to evaluate by numerical examples (Mackey-Glass chaotic time series and sunspot number forecasting). The performance of the TNFS-MGCSE achieves excellently with other existing models in the simulations. (C) 2010 Elsevier Ltd. All rights reserved.
URI: http://dx.doi.org/10.1016/j.eswa.2010.01.003
http://hdl.handle.net/11536/5195
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2010.01.003
期刊: EXPERT SYSTEMS WITH APPLICATIONS
Volume: 37
Issue: 7
起始頁: 5320
結束頁: 5330
顯示於類別:期刊論文


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