DocumentCode
3026866
Title
Combinations of evolutionary algorithms and fuzzy systems: a survey
Author
Shi, Yuhui
Author_Institution
EDS Indianapolis Technol. Center, Carmel, IN, USA
fYear
1999
fDate
36342
Firstpage
610
Lastpage
614
Abstract
Lot of schemes to combine evolutionary algorithms and fuzzy systems have been reported in the literature in recent years. Evolutionary algorithms have been used to design fuzzy systems and fuzzy systems have been utilized to adapt the evolutionary algorithms. Both sides interact with each other both supportively and collaboratively. We provide a survey with focus on evolutionary algorithms as supporting tools for designing fuzzy systems since this is the main research work reported in the literature. The survey is organized from three perspectives: homogeneous vs. heterogeneous representation; online learning vs. offline learning; static learning vs. adaptive learning algorithms
Keywords
evolutionary computation; fuzzy systems; knowledge representation; learning (artificial intelligence); adaptive learning algorithms; evolutionary algorithms; fuzzy systems design; heterogeneous representation; offline learning; online learning; static learning; Algorithm design and analysis; Collaboration; Collaborative work; Dynamic range; Evolutionary computation; Fuzzy systems; Genetic mutations; Heuristic algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Information Processing Society, 1999. NAFIPS. 18th International Conference of the North American
Conference_Location
New York, NY
Print_ISBN
0-7803-5211-4
Type
conf
DOI
10.1109/NAFIPS.1999.781766
Filename
781766
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