Adaptive Case Based Reasoning for Fault Diagnosis

Yee, Pang Shen and Kiong, Loo Chu and Soong, Lim Way (2009) Adaptive Case Based Reasoning for Fault Diagnosis. In: International Conference of Soft Computing and Pattern Recognition, DEC 04-07, 2009 , Malacca, MALAYSIA.

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Official URL: http://dx.doi.org/10.1109/SoCPaR.2009.135

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.

Item Type: Conference or Workshop Item (Paper)
Subjects: T Technology > T Technology (General)
Q Science > QA Mathematics > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 23 Sep 2011 08:28
Last Modified: 23 Sep 2011 08:28
URI: http://shdl.mmu.edu.my/id/eprint/1931

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