{"title":"处理复杂问题的模糊逻辑:一些实际应用的例子","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":"{\"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}","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}
Fuzzy logic to cope with complex problems: some examples of real-world applications
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
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
