{"title":"A rough analysis method of multi-attribute decision making for handling decision system with incomplete information","authors":"Ming-li Hu, Sifeng Liu","doi":"10.1109/GSIS.2007.4443410","DOIUrl":null,"url":null,"abstract":"A rough analysis method based on extension of rough sets is proposed for handling multi-attribute decision making problems with preference and incomplete information. Firstly, the concept of generalized extended dominance relation is presented; secondly, the rough approximations of knowledge are obtained by generalized extended dominance relation and decision rules of classification are acquired; thirdly, new method proves to be the generalization of the existing method and its performance is studied by contrast analysis; finally, the feasibility and effectiveness of new method are demonstrated by an example.","PeriodicalId":445155,"journal":{"name":"2007 IEEE International Conference on Grey Systems and Intelligent Services","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE International Conference on Grey Systems and Intelligent Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GSIS.2007.4443410","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
A rough analysis method based on extension of rough sets is proposed for handling multi-attribute decision making problems with preference and incomplete information. Firstly, the concept of generalized extended dominance relation is presented; secondly, the rough approximations of knowledge are obtained by generalized extended dominance relation and decision rules of classification are acquired; thirdly, new method proves to be the generalization of the existing method and its performance is studied by contrast analysis; finally, the feasibility and effectiveness of new method are demonstrated by an example.
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