{"title":"基于灰色关联分析和案例推理的灰色直觉模糊决策方法","authors":"Lipeng Peng","doi":"10.1109/GSIS.2015.7301888","DOIUrl":null,"url":null,"abstract":"In this paper we study a decision making problem based on grey incidence analysis and case-based reasoning for grey intuitionistic fuzzy information, in which the information about attribute weight is completely unknown. In order to get the weight vector of the attribute, we establish an optimization model based on score function, grey incidence theory and the case-based reasoning method, by which the attribute weights can be determined. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.","PeriodicalId":246110,"journal":{"name":"2015 IEEE International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Grey intuitionistic fuzzy decision making method based on grey incidence analysis and case-based reasoning\",\"authors\":\"Lipeng Peng\",\"doi\":\"10.1109/GSIS.2015.7301888\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we study a decision making problem based on grey incidence analysis and case-based reasoning for grey intuitionistic fuzzy information, in which the information about attribute weight is completely unknown. In order to get the weight vector of the attribute, we establish an optimization model based on score function, grey incidence theory and the case-based reasoning method, by which the attribute weights can be determined. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.\",\"PeriodicalId\":246110,\"journal\":{\"name\":\"2015 IEEE International Conference on Grey Systems and Intelligent Services (GSIS)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE International Conference on Grey Systems and Intelligent Services (GSIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GSIS.2015.7301888\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Grey Systems and Intelligent Services (GSIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GSIS.2015.7301888","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Grey intuitionistic fuzzy decision making method based on grey incidence analysis and case-based reasoning
In this paper we study a decision making problem based on grey incidence analysis and case-based reasoning for grey intuitionistic fuzzy information, in which the information about attribute weight is completely unknown. In order to get the weight vector of the attribute, we establish an optimization model based on score function, grey incidence theory and the case-based reasoning method, by which the attribute weights can be determined. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.