DocumentCode
3317659
Title
Multiobjective Genetic Fuzzy Systems: Review and Future Research Directions
Author
Ishibuchi, Hisao
Author_Institution
Osaka Prefecture Univ., Osaka
fYear
2007
fDate
23-26 July 2007
Firstpage
1
Lastpage
6
Abstract
Evolutionary algorithms have been successfully used in many studies to design accurate and interpretable fuzzy systems under the name of genetic fuzzy systems. Recently evolutionary multiobjective algorithms have been used for interpretability-accuracy tradeoff analysis of fuzzy systems. We first review a wide range of related studies to multiobjective genetic fuzzy systems. Then we illustrate multiobjective design of fuzzy systems through computational experiments on some benchmark data sets. Finally we point out promising future research directions.
Keywords
fuzzy systems; genetic algorithms; benchmark data sets; evolutionary multiobjective algorithms; interpretability-accuracy tradeoff analysis; multiobjective genetic fuzzy systems; Algorithm design and analysis; Computer science; Evolutionary computation; Fuzzy neural networks; Fuzzy systems; Genetics; Intelligent systems; Neural networks; Partitioning algorithms; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems Conference, 2007. FUZZ-IEEE 2007. IEEE International
Conference_Location
London
ISSN
1098-7584
Print_ISBN
1-4244-1209-9
Electronic_ISBN
1098-7584
Type
conf
DOI
10.1109/FUZZY.2007.4295487
Filename
4295487
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