{"title":"二类模糊逻辑动态参数自适应的模糊微分演化新方法","authors":"Patricia Ochoa, O. Castillo, J. Soria","doi":"10.1109/NAFIPS.2016.7851594","DOIUrl":null,"url":null,"abstract":"In this paper we consider the Differential Evolution (DE) algorithm by using fuzzy logic to make dynamic changes in the mutation parameter (F), and this modification of the algorithm we call the Fuzzy Differential Evolution algorithm (FDE). A comparison of the FDE algorithm using type 1 fuzzy logic and interval type-2 fuzzy logic is performed for a set of Benchmark functions.","PeriodicalId":208265,"journal":{"name":"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Type-2 fuzzy logic dynamic parameter adaptation in a new Fuzzy Differential Evolution method\",\"authors\":\"Patricia Ochoa, O. Castillo, J. Soria\",\"doi\":\"10.1109/NAFIPS.2016.7851594\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we consider the Differential Evolution (DE) algorithm by using fuzzy logic to make dynamic changes in the mutation parameter (F), and this modification of the algorithm we call the Fuzzy Differential Evolution algorithm (FDE). A comparison of the FDE algorithm using type 1 fuzzy logic and interval type-2 fuzzy logic is performed for a set of Benchmark functions.\",\"PeriodicalId\":208265,\"journal\":{\"name\":\"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAFIPS.2016.7851594\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAFIPS.2016.7851594","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Type-2 fuzzy logic dynamic parameter adaptation in a new Fuzzy Differential Evolution method
In this paper we consider the Differential Evolution (DE) algorithm by using fuzzy logic to make dynamic changes in the mutation parameter (F), and this modification of the algorithm we call the Fuzzy Differential Evolution algorithm (FDE). A comparison of the FDE algorithm using type 1 fuzzy logic and interval type-2 fuzzy logic is performed for a set of Benchmark functions.
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