DocumentCode :
3065149
Title :
Hybrid Intelligent Diagnosis Systems
Author :
Chohra, Amine ; Kanaoui, Nadia ; Madani, Kurosh
Author_Institution :
Paris XII Univ., Lieusaint
fYear :
2007
fDate :
28-30 June 2007
Firstpage :
115
Lastpage :
120
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.
Keywords :
fault diagnosis; knowledge representation; pattern classification; biomedicine applications; decision-making; hybrid intelligent diagnosis systems; industrial applications; information fusion; knowledge classification; knowledge representation; reliability degree; Application software; Biological neural networks; Biomedical computing; Computer networks; Decision making; Fault diagnosis; Fuzzy logic; Hybrid intelligent systems; Intelligent systems; Knowledge representation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Information Systems and Industrial Management Applications, 2007. CISIM '07. 6th International Conference on
Conference_Location :
Minneapolis, MN
Print_ISBN :
0-7695-2894-5
Type :
conf
DOI :
10.1109/CISIM.2007.36
Filename :
4273506
Link To Document :
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