Fault diagnosis method based on PSO-optimized H-BP neural network

Authors:
Rao Hong;Li Meizhu;Hu Qianru
Affiliations:
Center of Computer, Nanchang University, Nanchang, Jiangxi Province, China;International Exchange College, Nanchang University, Nanchang, Jiangxi Province, China;Center of Computer, Nanchang University, Nanchang, Jiangxi Province, China
Venue:
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
Year:
2009

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Abstract

The paper combined the advantage of Particle Swarm Optimization algorithm (PSO), the global optimizing ability of Hopfield Neural Network, and the teacher supervising features of BP neural network to construct a new equipment fault diagnosis method with higher diagnosis precision, compared with the traditional single BP neural network.