{"title":"Hybrid Intelligent Diagnosis Systems","authors":"A. Chohra, N. Kanaoui, K. Madani","doi":"10.1109/CISIM.2007.36","DOIUrl":null,"url":null,"abstract":"In this paper, the main objective is to give a methodology to design hybrid intelligent diagnosis systems for a large field of biomedicine and industrial applications. At first, a brief description on diagnosis tasks in such applications is presented. Second, diagnosis systems are presented. Third, the main steps of hybrid intelligent diagnosis systems are developed, for each step emphasizing problems and suggesting solutions able to ensure the design of hybrid intelligent diagnosis systems with a satisfactory reliability degree. In fact, the main steps discussed are knowledge representation, classification, classifier issued information fusion, and decision-making. Finally, a discussion is given with regard to the suggested methodology.","PeriodicalId":350490,"journal":{"name":"6th International Conference on Computer Information Systems and Industrial Management Applications (CISIM'07)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"6th International Conference on Computer Information Systems and Industrial Management Applications (CISIM'07)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISIM.2007.36","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
In this paper, the main objective is to give a methodology to design hybrid intelligent diagnosis systems for a large field of biomedicine and industrial applications. At first, a brief description on diagnosis tasks in such applications is presented. Second, diagnosis systems are presented. Third, the main steps of hybrid intelligent diagnosis systems are developed, for each step emphasizing problems and suggesting solutions able to ensure the design of hybrid intelligent diagnosis systems with a satisfactory reliability degree. In fact, the main steps discussed are knowledge representation, classification, classifier issued information fusion, and decision-making. Finally, a discussion is given with regard to the suggested methodology.