{"title":"Fuzzy logic to cope with complex problems: some examples of real-world applications","authors":"B. Bouchon-Meunier","doi":"10.1145/1456223.1456306","DOIUrl":null,"url":null,"abstract":"In this paper, we present the capabilities of fuzzy logic to cope with complex problems and to summarize or synthetize large amounts of data. We first describe the major theoretical tools we mainly use, namely similarity measures and fuzzy inductive learning, and then their applications on several examples that illustrate various aspects of a fuzzy set based knowledge representation","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Soft Computing as Transdisciplinary Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1456223.1456306","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we present the capabilities of fuzzy logic to cope with complex problems and to summarize or synthetize large amounts of data. We first describe the major theoretical tools we mainly use, namely similarity measures and fuzzy inductive learning, and then their applications on several examples that illustrate various aspects of a fuzzy set based knowledge representation
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