DocumentCode :
3039270
Title :
Research and Design of Extension Case Base Based on CBR
Author :
Han, Dan ; Ni, Zhiwei ; Zhang, Gongrang ; Wang, Hongyu ; Yan, Jun
Author_Institution :
Lab. of Process Optimization & Intell. Decision-making, Hefei Univ. of Technol., Hefei, China
fYear :
2009
fDate :
24-26 July 2009
Firstpage :
210
Lastpage :
214
Abstract :
In order to solve the problems that there is less valid information on the vehicle maintenance and the intelligent fault diagnosis system is inefficient with increasing the case base, based on case based reasoning (CBR). Extenics is used in designing case base. Firstly, extension model and binary tree are used for the formal description, as the mode of knowledge representation. Secondly, extension reasoning is applied to extending the case base. Last, customerspsila feedbacks with the new case are made use of maintaining the case base, to complete the machine learning. The extension case base is built to conveniently classify, retrieve and maintain the case. Thus, the efficiency and flexibility of the intelligent system is improved together.
Keywords :
case-based reasoning; knowledge representation; learning (artificial intelligence); traffic engineering computing; vehicles; case based reasoning; intelligent fault diagnosis system; knowledge representation; machine learning; vehicle maintenance process; Artificial intelligence; Automotive engineering; Conference management; Design engineering; Fault diagnosis; Financial management; Information retrieval; Intelligent systems; Intelligent vehicles; Knowledge representation; CBR; Extenics; Extension Case Base; Knowledge Representation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Business Intelligence and Financial Engineering, 2009. BIFE '09. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-0-7695-3705-4
Type :
conf
DOI :
10.1109/BIFE.2009.57
Filename :
5208901
Link To Document :
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