{"title":"GA to optimize approximate solutions of fuzzy relational equations for fuzzy systems or controllers","authors":"M. Negoita, M. Giuclea","doi":"10.1109/ANNES.1995.499455","DOIUrl":null,"url":null,"abstract":"A GA (genetic algorithm) method for discrete time fuzzy model identification is proposed. The approach consists of three levels of optimization in order to minimize a quadratic performance index. Two numerical examples prove the applicability of this simultaneous optimization of the mentioned levels by GA.","PeriodicalId":123427,"journal":{"name":"Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ANNES.1995.499455","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
A GA (genetic algorithm) method for discrete time fuzzy model identification is proposed. The approach consists of three levels of optimization in order to minimize a quadratic performance index. Two numerical examples prove the applicability of this simultaneous optimization of the mentioned levels by GA.
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