{"title":"Generalized method of fuzzy interpolative-type reasoning based on lagrange's interpolation","authors":"Baowen Wang, Xiaodong Shao, Wenyuan Liu, Yan Shi","doi":"10.1109/ICIMA.2004.1384321","DOIUrl":null,"url":null,"abstract":"When fuvy rule base is sparse, reference (I) proposed a fuzzy interpolative-type reasoning based on Lagrange's interpolation. This fuzzy reasoning method can guarantee the membership function of the inference consequence to be of ~iamgular-fypeiiall ofmembership fyDEtiDllE dfuuy rules and an Observation are given by triangular-type when fuzzy rule base is sparse. But to many membership functions of other type, this method is not applicable. We generalized this method so that this method is applicable to most normal convex fuzzy sets.","PeriodicalId":375056,"journal":{"name":"2004 International Conference on Intelligent Mechatronics and Automation, 2004. Proceedings.","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 International Conference on Intelligent Mechatronics and Automation, 2004. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIMA.2004.1384321","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
When fuvy rule base is sparse, reference (I) proposed a fuzzy interpolative-type reasoning based on Lagrange's interpolation. This fuzzy reasoning method can guarantee the membership function of the inference consequence to be of ~iamgular-fypeiiall ofmembership fyDEtiDllE dfuuy rules and an Observation are given by triangular-type when fuzzy rule base is sparse. But to many membership functions of other type, this method is not applicable. We generalized this method so that this method is applicable to most normal convex fuzzy sets.
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