FUZZY SYSTEM FOR AUTOMOTIVE FAULT DIAGNOSIS : FAST RULE GENERATION AND SELF-TUNING
In this paper, the authors describe a fuzzy model which uses machine learning techniques to learn automotive diagnostic knowledge. The model contains algorithms which automatically generate fuzzy rules and optimizing fuzzy membership functions. The authors describe the application of the fuzzy model to detect vacuum leaks in electronic engine controllers at automotive assembly plants. Test results and performance are discussed.
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Supplemental Notes:
- Publication Date: March 2000
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Corporate Authors:
Jamiah al-Lubnaniyah al-Amirikiyah
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Authors:
- Li, Yi
- Chen, Tie Qi
- Hamilton, Brennan
- Publication Date: 2000
Language
- English
Media Info
- Pagination: p. 651-660
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Serial:
- IEEE transactions on vehicular technology. Vol. 49, no. 2
- Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Subject/Index Terms
- TRT Terms: Electronic equipment; Fault monitoring; Fuzzy logic; Fuzzy systems; Vehicle body parts; Vehicle components
- Subject Areas: Vehicles and Equipment;
Filing Info
- Accession Number: 00799918
- Record Type: Publication
- Source Agency: UC Berkeley Transportation Library
- Files: PATH
- Created Date: Oct 12 2000 12:00AM