{"title":"模糊集是模糊连续的","authors":"J. Paetz","doi":"10.1109/NAFIPS.2003.1226790","DOIUrl":null,"url":null,"abstract":"In a classical arrangement we have on the one hand discrete symbolic and on the other hand continous numerical data attributes. The following evident questions arise: How can fuzzy sets be integrated in this classical schema? Are fuzzy sets discrete and/or continous? Can we measure how discrete, or continous, respectively, an attribute is? We will present the idea that fuzzy sets are continous and discrete sets with a certain degree by using a visualization technique. We measure continuity of a fuzzy set M by an area q(M)/spl isin/[0,1], that will be defined. If q(M)=0, then M is discrete. If q(M)=1, then it is continous. If q(M) is in (0,1), then M is defined as fuzzy-continous. Thus, a non-degenerated fuzzy set is a fuzzy-continous set. The value q(M) is a natural measure for fuzzy-continuity and 1-q(M) for fuzzy discreteness. Additionally to our theoretical consideration we will give some visualized examples.","PeriodicalId":153530,"journal":{"name":"22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fuzzy sets are fuzzy-continous\",\"authors\":\"J. Paetz\",\"doi\":\"10.1109/NAFIPS.2003.1226790\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In a classical arrangement we have on the one hand discrete symbolic and on the other hand continous numerical data attributes. The following evident questions arise: How can fuzzy sets be integrated in this classical schema? Are fuzzy sets discrete and/or continous? Can we measure how discrete, or continous, respectively, an attribute is? We will present the idea that fuzzy sets are continous and discrete sets with a certain degree by using a visualization technique. We measure continuity of a fuzzy set M by an area q(M)/spl isin/[0,1], that will be defined. If q(M)=0, then M is discrete. If q(M)=1, then it is continous. If q(M) is in (0,1), then M is defined as fuzzy-continous. Thus, a non-degenerated fuzzy set is a fuzzy-continous set. The value q(M) is a natural measure for fuzzy-continuity and 1-q(M) for fuzzy discreteness. Additionally to our theoretical consideration we will give some visualized examples.\",\"PeriodicalId\":153530,\"journal\":{\"name\":\"22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-07-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAFIPS.2003.1226790\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAFIPS.2003.1226790","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In a classical arrangement we have on the one hand discrete symbolic and on the other hand continous numerical data attributes. The following evident questions arise: How can fuzzy sets be integrated in this classical schema? Are fuzzy sets discrete and/or continous? Can we measure how discrete, or continous, respectively, an attribute is? We will present the idea that fuzzy sets are continous and discrete sets with a certain degree by using a visualization technique. We measure continuity of a fuzzy set M by an area q(M)/spl isin/[0,1], that will be defined. If q(M)=0, then M is discrete. If q(M)=1, then it is continous. If q(M) is in (0,1), then M is defined as fuzzy-continous. Thus, a non-degenerated fuzzy set is a fuzzy-continous set. The value q(M) is a natural measure for fuzzy-continuity and 1-q(M) for fuzzy discreteness. Additionally to our theoretical consideration we will give some visualized examples.