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
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