Study on case-based reasoning expert system about the matching optimization of particle swarm optimization algorithm

For the weak of the traditional expert system reasoning ability and intelligent level, the problem of the matching expression of the traditional expert system in the reasoning ability and case is solved by using the particle swarm method in this paper. The basic principle and mathematical expression...

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Bibliographic Details
Published in2015 Prognostics and System Health Management Conference (PHM) pp. 1 - 4
Main Authors Yu, Dequan, Lv, Chuan, Wu, QuanLei, Peng, Xu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2015
Subjects
Atmospheric modeling
Cognition
Expert system
Expert systems
Integrated circuits
keywords importance degree
Particle swarm method
Particle swarm optimization
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DOI10.1109/PHM.2015.7380047

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Summary:For the weak of the traditional expert system reasoning ability and intelligent level, the problem of the matching expression of the traditional expert system in the reasoning ability and case is solved by using the particle swarm method in this paper. The basic principle and mathematical expression of the particle swarm expert system are described in detail in this paper. By building reasonable keyword importance model, we decide which case adaptation is the highest according to the overall matching value. Finally, the combination of the case and the realization of t he particle swarm optimization algorithm are carried out.
DOI:10.1109/PHM.2015.7380047