{"title":"X-mu方法:模糊量、模糊算法和模糊关联规则","authors":"T. Martin, B. Azvine","doi":"10.1109/FOCI.2013.6602451","DOIUrl":null,"url":null,"abstract":"The use of so-called fuzzy numbers for approximate calculations leads to significant problems, because the underlying mathematical structure is weaker than ordinary arithmetic. Many of these problems arise from the fact that the fuzzy quantities are actually fuzzy intervals. Gradual numbers were recently proposed as a better representation for fuzzy quantities. In this paper, we describe the X-μ approach, a new method of visualizing and calculating functions of fuzzy quantities. In particular, we illustrate the calculation of fuzzy association confidence in cases where membership can be represented by a function or a table of values.","PeriodicalId":237129,"journal":{"name":"2013 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","volume":"13 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"The X-mu approach: Fuzzy quantities, fuzzy arithmetic and fuzzy association rules\",\"authors\":\"T. Martin, B. Azvine\",\"doi\":\"10.1109/FOCI.2013.6602451\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The use of so-called fuzzy numbers for approximate calculations leads to significant problems, because the underlying mathematical structure is weaker than ordinary arithmetic. Many of these problems arise from the fact that the fuzzy quantities are actually fuzzy intervals. Gradual numbers were recently proposed as a better representation for fuzzy quantities. In this paper, we describe the X-μ approach, a new method of visualizing and calculating functions of fuzzy quantities. In particular, we illustrate the calculation of fuzzy association confidence in cases where membership can be represented by a function or a table of values.\",\"PeriodicalId\":237129,\"journal\":{\"name\":\"2013 IEEE Symposium on Foundations of Computational Intelligence (FOCI)\",\"volume\":\"13 2\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-04-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE Symposium on Foundations of Computational Intelligence (FOCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FOCI.2013.6602451\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FOCI.2013.6602451","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The X-mu approach: Fuzzy quantities, fuzzy arithmetic and fuzzy association rules
The use of so-called fuzzy numbers for approximate calculations leads to significant problems, because the underlying mathematical structure is weaker than ordinary arithmetic. Many of these problems arise from the fact that the fuzzy quantities are actually fuzzy intervals. Gradual numbers were recently proposed as a better representation for fuzzy quantities. In this paper, we describe the X-μ approach, a new method of visualizing and calculating functions of fuzzy quantities. In particular, we illustrate the calculation of fuzzy association confidence in cases where membership can be represented by a function or a table of values.