遗传算法优化模糊系统或控制器的模糊关系方程的近似解

Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems Pub Date : 1995-11-20 DOI:10.1109/ANNES.1995.499455

M. Negoita, M. Giuclea

{"title":"遗传算法优化模糊系统或控制器的模糊关系方程的近似解","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":"{\"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}","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

摘要

提出了一种基于遗传算法的离散时间模糊模型辨识方法。该方法包括三个层次的优化，以最小化二次性能指标。两个算例证明了用遗传算法同时优化上述层次的适用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

GA to optimize approximate solutions of fuzzy relational equations for fuzzy systems or controllers

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.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems

自引率

0.00%

发文量