{"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}
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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.
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模糊集是模糊连续的
在经典排列中,我们一方面有离散的符号数据属性,另一方面有连续的数值数据属性。下面这些明显的问题出现了:模糊集合如何在这个经典图式中被整合?模糊集是离散的还是连续的?我们能分别度量一个属性是离散的还是连续的吗?我们将利用可视化的方法,提出模糊集是一定程度的连续集和离散集的概念。我们用一个面积q(M)/spl isin/[0,1]来度量模糊集M的连续性,该面积将被定义。如果q(M)=0,则M是离散的。如果q(M)=1,则它是连续的。若q(M)在(0,1)内,则M定义为模糊连续。因此,一个不退化的模糊集是一个模糊连续集。q(M)是模糊连续性和1-q(M)的自然测度。除了我们的理论考虑,我们将给出一些可视化的例子。
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