{"title":"基于粗糙集和条件信息熵的信息系统评价研究","authors":"Sha Fu, Guang Sun, Hangjun Zhou, Feng Yan","doi":"10.3923/JSE.2016.129.137","DOIUrl":null,"url":null,"abstract":"Based on the incompleteness and conceptual uncertainty of information in management decision making and evaluation, the rough set theory and condition information entropy were introduced to build a comprehensive evaluation model based on the rough set condition information entropy, so as to present the tendency of experts’ experience and knowledge towards index importance. To solve the problem of index weight acquisition in that system, the decision table was partitioned according by analyzing and evaluating characteristics of the small and medium sample data according to the factual condition, so as to obtain its weight value in an objective manner through hierarchical calculation method from the aspect of information entropy and eventually obtain the comprehensive evaluation result of the information system. Through real case analysis, the feasibility and effectiveness of the rough set intelligent evaluation model were verified.","PeriodicalId":30943,"journal":{"name":"Journal of Software Engineering","volume":"10 1","pages":"129-137"},"PeriodicalIF":0.0000,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"An Evaluation Study on Information System Based on Rough Set and Condition Information Entropy\",\"authors\":\"Sha Fu, Guang Sun, Hangjun Zhou, Feng Yan\",\"doi\":\"10.3923/JSE.2016.129.137\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the incompleteness and conceptual uncertainty of information in management decision making and evaluation, the rough set theory and condition information entropy were introduced to build a comprehensive evaluation model based on the rough set condition information entropy, so as to present the tendency of experts’ experience and knowledge towards index importance. To solve the problem of index weight acquisition in that system, the decision table was partitioned according by analyzing and evaluating characteristics of the small and medium sample data according to the factual condition, so as to obtain its weight value in an objective manner through hierarchical calculation method from the aspect of information entropy and eventually obtain the comprehensive evaluation result of the information system. Through real case analysis, the feasibility and effectiveness of the rough set intelligent evaluation model were verified.\",\"PeriodicalId\":30943,\"journal\":{\"name\":\"Journal of Software Engineering\",\"volume\":\"10 1\",\"pages\":\"129-137\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Software Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3923/JSE.2016.129.137\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3923/JSE.2016.129.137","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Evaluation Study on Information System Based on Rough Set and Condition Information Entropy
Based on the incompleteness and conceptual uncertainty of information in management decision making and evaluation, the rough set theory and condition information entropy were introduced to build a comprehensive evaluation model based on the rough set condition information entropy, so as to present the tendency of experts’ experience and knowledge towards index importance. To solve the problem of index weight acquisition in that system, the decision table was partitioned according by analyzing and evaluating characteristics of the small and medium sample data according to the factual condition, so as to obtain its weight value in an objective manner through hierarchical calculation method from the aspect of information entropy and eventually obtain the comprehensive evaluation result of the information system. Through real case analysis, the feasibility and effectiveness of the rough set intelligent evaluation model were verified.