关键词: 改进BP网络, 粒子群算法, 辨识, 参数优化

Abstract: After type and structure of identification neural network have been determined，identification effect can be directly influenced by identification parameters like neural network weighting initial value.However，it’s hard to acquire satisfactory identification performance with parameters determined by method of trial and error according to experience.Aiming at this problem，an identification method combining Particle Swarm Optimization（PSO） algorithm and improved BP Neural Network（NN） introducing momentum coefficient in learning algorithm is put forward.This method uses particle swarm optimization algorithm to optimize the parameters of NN weighting initial value，NN offset initial value，speed of learning and momentum coefficient in using improved BP neural network to identify.Subsequently，the optimized neural network model is modified in control system，which perfects the identification model.The application in thermal process shows the identification method is effective.

Key words: improved BP Neural Network（NN）, Particle Swarm Optimization（PSO）, identification, optimization of parameters