{"title":"基于Mamdani模糊逻辑系统和遗传算法的模糊分类器","authors":"Zhou Weihong, Xiong Shunqing, Ma Ting","doi":"10.1109/YCICT.2010.5713079","DOIUrl":null,"url":null,"abstract":"Most of the fuzzy classifiers are created by fuzzy rules based on apriori knowledge and expert's knowledge, but in many applications, it's difficult to obtain fuzzy rules without apriori knowledge of the data. To solve this problem, a new way of creating Mamdani fuzzy classifier based on Mamdani fuzzy logical system is proposesed in this paper, and the new fuzzy classifier is improved with the genetic algorithm further. The result of data simulation with Iris data shows the new Mamdani fuzzy classifier has minimum number of features, minimum number of fuzzy rules and better precision.","PeriodicalId":179847,"journal":{"name":"2010 IEEE Youth Conference on Information, Computing and Telecommunications","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"A fuzzy classifier based on Mamdani fuzzy logic system and genetic algorithm\",\"authors\":\"Zhou Weihong, Xiong Shunqing, Ma Ting\",\"doi\":\"10.1109/YCICT.2010.5713079\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Most of the fuzzy classifiers are created by fuzzy rules based on apriori knowledge and expert's knowledge, but in many applications, it's difficult to obtain fuzzy rules without apriori knowledge of the data. To solve this problem, a new way of creating Mamdani fuzzy classifier based on Mamdani fuzzy logical system is proposesed in this paper, and the new fuzzy classifier is improved with the genetic algorithm further. The result of data simulation with Iris data shows the new Mamdani fuzzy classifier has minimum number of features, minimum number of fuzzy rules and better precision.\",\"PeriodicalId\":179847,\"journal\":{\"name\":\"2010 IEEE Youth Conference on Information, Computing and Telecommunications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE Youth Conference on Information, Computing and Telecommunications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/YCICT.2010.5713079\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE Youth Conference on Information, Computing and Telecommunications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/YCICT.2010.5713079","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A fuzzy classifier based on Mamdani fuzzy logic system and genetic algorithm
Most of the fuzzy classifiers are created by fuzzy rules based on apriori knowledge and expert's knowledge, but in many applications, it's difficult to obtain fuzzy rules without apriori knowledge of the data. To solve this problem, a new way of creating Mamdani fuzzy classifier based on Mamdani fuzzy logical system is proposesed in this paper, and the new fuzzy classifier is improved with the genetic algorithm further. The result of data simulation with Iris data shows the new Mamdani fuzzy classifier has minimum number of features, minimum number of fuzzy rules and better precision.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
