{"title":"基于粗糙集的gds多类型偏好信息集成方法","authors":"Tian Fei, Liu Lu, You Weijia","doi":"10.1109/GSIS.2007.4443406","DOIUrl":null,"url":null,"abstract":"Two problems in multi-attribute group decision process are studied: integration of multi-types of preference information and making use of given decisions. And a GDSS model based on rough set is proposed, which includes seven common ways for representing preference information. An improved Sem Naive Scaler Algorithm is also suggested to decentralize the information in the rough set table. Finally, rules based on dominance-based rough set theory are applied to the information table to rank all the alternatives.","PeriodicalId":445155,"journal":{"name":"2007 IEEE International Conference on Grey Systems and Intelligent Services","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A rough set based GDSS approach to integrate multi-type preference information\",\"authors\":\"Tian Fei, Liu Lu, You Weijia\",\"doi\":\"10.1109/GSIS.2007.4443406\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Two problems in multi-attribute group decision process are studied: integration of multi-types of preference information and making use of given decisions. And a GDSS model based on rough set is proposed, which includes seven common ways for representing preference information. An improved Sem Naive Scaler Algorithm is also suggested to decentralize the information in the rough set table. Finally, rules based on dominance-based rough set theory are applied to the information table to rank all the alternatives.\",\"PeriodicalId\":445155,\"journal\":{\"name\":\"2007 IEEE International Conference on Grey Systems and Intelligent Services\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"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.2007.4443406\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE International Conference on Grey Systems and Intelligent Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GSIS.2007.4443406","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A rough set based GDSS approach to integrate multi-type preference information
Two problems in multi-attribute group decision process are studied: integration of multi-types of preference information and making use of given decisions. And a GDSS model based on rough set is proposed, which includes seven common ways for representing preference information. An improved Sem Naive Scaler Algorithm is also suggested to decentralize the information in the rough set table. Finally, rules based on dominance-based rough set theory are applied to the information table to rank all the alternatives.
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