DocumentCode :
2940482
Title :
Adaptive Case Based Reasoning for Fault Diagnosis
Author :
Yee, Pang Shen ; Kiong, Loo Chu ; Soong, Lim Way
Author_Institution :
Fac. of Eng. & Technol., Multimedia Univ., Cyberjaya, Malaysia
fYear :
2009
fDate :
4-7 Dec. 2009
Firstpage :
678
Lastpage :
681
Abstract :
A hybrid system of case based reasoning (CBR) with fuzzy ARTMAP (FAM) has been proposed to perform fault diagnosis for actuator system in DAMADICS benchmark. The hybrid system of CBR and FAM is for undertaking the stability plasticity dilemma for the incremental learning problem in CBR. At the same time, FAM can overcome the difficulty of indexing and retrieval in CBR as well as adaption of cases. FAM is used to make hypotheses and to guide the search of similar cases in the library, while CBR is used to select the most similar match for a given problem, supporting a particular hypothesis. A CBR system supports problem solving based on past experience with similar decision problems. The main strength lies in the fact that it enables directly reusing concrete examples in history and consequently eases the knowledge acquisition bottleneck.
Keywords :
case-based reasoning; fuzzy set theory; knowledge acquisition; DAMADICS; adaptive case-based reasoning; fault diagnosis; fuzzy ARTMAP; knowledge acquisition; Actuators; Concrete; Fault diagnosis; Fuzzy reasoning; Fuzzy systems; History; Indexing; Libraries; Problem-solving; Stability; DAMADICS Benchmark; case based reasoning; fault diagnosis; fuzzy ARTMAP; hybrid system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Soft Computing and Pattern Recognition, 2009. SOCPAR '09. International Conference of
Conference_Location :
Malacca
Print_ISBN :
978-1-4244-5330-6
Electronic_ISBN :
978-0-7695-3879-2
Type :
conf
DOI :
10.1109/SoCPaR.2009.135
Filename :
5370970
Link To Document :
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