Title :
Multiobjective Genetic Fuzzy Systems: Review and Future Research Directions
Author :
Ishibuchi, Hisao
Author_Institution :
Osaka Prefecture Univ., Osaka
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;
Conference_Titel :
Fuzzy Systems Conference, 2007. FUZZ-IEEE 2007. IEEE International
Conference_Location :
London
Print_ISBN :
1-4244-1209-9
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZY.2007.4295487
