{"title":"模糊软集与综合模糊集的关系","authors":"Yi Jiang, Hailiang Zhao, Junxuan He","doi":"10.1109/ISKE.2017.8258761","DOIUrl":null,"url":null,"abstract":"Fuzzy set can be divided into single parameter or multi-parameter's ones with which to depict their fuzzy attributes. In references, it is usual defined in a single parameter universe and yet multi-parameter's ones often appears in so-called fuzzy relation. Fuzzy soft set can be used to describe a fuzzy object by aggregating fuzzy parameters in different attributes. Fuzzy set can be employed to do the same things. It can be concluded that there must be a certain relation between the two concepts. And to give the relation, integrative fuzzy set is proposed in this paper. And which can be decomposed into a fuzzy soft set under certain condition. Fuzzy soft set also can be translated into an integrative fuzzy set by some operator. Both of them can be used for decision-making. Theoretical analysis and examples show the optimal decision-making results are equivalent.","PeriodicalId":208009,"journal":{"name":"2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The relation between fuzzy soft set and integrative fuzzy set\",\"authors\":\"Yi Jiang, Hailiang Zhao, Junxuan He\",\"doi\":\"10.1109/ISKE.2017.8258761\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fuzzy set can be divided into single parameter or multi-parameter's ones with which to depict their fuzzy attributes. In references, it is usual defined in a single parameter universe and yet multi-parameter's ones often appears in so-called fuzzy relation. Fuzzy soft set can be used to describe a fuzzy object by aggregating fuzzy parameters in different attributes. Fuzzy set can be employed to do the same things. It can be concluded that there must be a certain relation between the two concepts. And to give the relation, integrative fuzzy set is proposed in this paper. And which can be decomposed into a fuzzy soft set under certain condition. Fuzzy soft set also can be translated into an integrative fuzzy set by some operator. Both of them can be used for decision-making. Theoretical analysis and examples show the optimal decision-making results are equivalent.\",\"PeriodicalId\":208009,\"journal\":{\"name\":\"2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISKE.2017.8258761\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISKE.2017.8258761","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The relation between fuzzy soft set and integrative fuzzy set
Fuzzy set can be divided into single parameter or multi-parameter's ones with which to depict their fuzzy attributes. In references, it is usual defined in a single parameter universe and yet multi-parameter's ones often appears in so-called fuzzy relation. Fuzzy soft set can be used to describe a fuzzy object by aggregating fuzzy parameters in different attributes. Fuzzy set can be employed to do the same things. It can be concluded that there must be a certain relation between the two concepts. And to give the relation, integrative fuzzy set is proposed in this paper. And which can be decomposed into a fuzzy soft set under certain condition. Fuzzy soft set also can be translated into an integrative fuzzy set by some operator. Both of them can be used for decision-making. Theoretical analysis and examples show the optimal decision-making results are equivalent.