计算机科学 ›› 2012, Vol. 39 ›› Issue (Z6): 449-451.

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基于微粒群优化神经网络算法的研究与仿真

蔡智仁   

  1. (福建省特种设备检验研究院莆田分院 莆田351100)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Research and Simulation of Algorithm Based on Particle Swarm Optimizing Neural Network

  • Online:2018-11-16 Published:2018-11-16

摘要: 微粒群优化((PSO)算法作为一种新兴的群智能优化算法,引起了不少人的注意和研究。主要研究微粒群优化算法与神经网络相结合形成的一种新颖的算法,并将其应用于永磁同步电机的混沌控制,实现其混沌控制。实验结果表明该算法具有一定的可行性,也说明了微粒群优化神经网络算法在现实中具有一定的实际价值。

关键词: 微粒群,神经网络,永磁同步电机,混沌

Abstract: As a new swarm itelligent algorithm, Particle Swarm Optimization(PSO ) algorithm has been attented and studied by many people. This paper mainly studied on the new algorithm that formed by PSO combining with neural network. Taking chaos phenomina of permanent magnet synchronous motor as a object, the new algorithm achieves controlling it. I}hc results of the expriments indicate the algorithm is feasible. At the same time, It proves the PSO optimizing neural network having some actural value.

Key words: Particle swarm optimization(PSO) , Neural network, Permanent magnet synchronous motor, Chaos

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