Title :
Research upon Fault Diagnosis Expert System Based on Fuzzy Neural Network
Author :
Kun, Yang ; Guangyao, Ouyang ; Lina, Ye
Author_Institution :
Power Eng. Dept., Naval Univ. of Eng., Wuhan, China
Abstract :
The traditional Expert System has many shortcomings, for instance, its weak knowledge acquisition capability and empirical knowledgepsilas expression uncertainty. To solve these bottleneck problems, A strategy on fault diagnosis expert system which is based upon fuzzy theory and ANN(ANN:artificial neural network) technique is put forward in this paper, as also its principle, construction, algorithm are all presented. Its performance has been proved to be very excellent when used upon the diesel fuel system classified fault diagnosis.
Keywords :
expert systems; fault diagnosis; fuzzy set theory; neural nets; artificial neural network; expert system; fault diagnosis; fuzzy neural network; fuzzy theory; knowledge acquisition; Artificial neural networks; Diagnostic expert systems; Electronic mail; Fault diagnosis; Fuzzy neural networks; Fuzzy systems; Humans; Knowledge acquisition; Knowledge engineering; Power engineering and energy;
Conference_Titel :
Information Engineering, 2009. ICIE '09. WASE International Conference on
Conference_Location :
Taiyuan, Shanxi
Print_ISBN :
978-0-7695-3679-8
DOI :
10.1109/ICIE.2009.136