Research on Inference Engine of Vehicle Fault Diagnosis Expert System

DOI

10.2991/ameii-15.2015.270How to use a DOI?

Keywords

optimized inference engine; expert system; vehicle; fault diagnosis.

Abstract

To solve the problem of efficient reasoning and self-learning ability in expert system containing production representation knowledge, paper proposed an approach, sort-selection algorithm, to optimize the process of sort and, updated the confidence of all the knowledge according to frequency of the selection user chooses to realize the self-learning ability for expert system. Paper discussed the theory and process of the approach and applied it to the Vehicle Fault Diagnose Expert System. The testing result shows that these approaches could be easily realized and improved the efficiency of vehicle fault diagnosis.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zhiyu Huang
AU  - Xi Peng
PY  - 2015/04
DA  - 2015/04
TI  - Research on Inference Engine of Vehicle Fault Diagnosis Expert System
BT  - Proceedings of the International Conference on Advances in Mechanical Engineering and Industrial Informatics
PB  - Atlantis Press
SP  - 1466
EP  - 1471
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-15.2015.270
DO  - 10.2991/ameii-15.2015.270
ID  - Huang2015/04
ER  -