Fuzzy Rule Selection Using Evolutionary Multiobjective Optimization Methods
Published in Transactions of the Institute of Systems Control and Information Engineers • Jan 1, 2004
NobleIDNI2P70W29R05S07
Authors:,
Takashi Yamamoto
Hisao Ishibuchi
Abstract
One advantage of evolutionary multiobjective optimization (EMO) algorithms over classical approaches is that many non-dominated solutions can be simultaneously obtained by their single run. This paper shows how this advantage can be utilized in genetic rule selection for the design of fuzzy rule-bas...
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