BP networks training algorithm based on particle swarm optimization

Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (9): 67-69.

• 理论研究 • Previous Articles Next Articles

BP networks training algorithm based on particle swarm optimization

PAN Hao,HAN Xiao-lei

College of Computer Science，Wuhan University of Technology，Wuhan 430070，China

Received:2007-07-16 Revised:2007-10-15 Online:2008-03-21 Published:2008-03-21
Contact: PAN Hao

粒子群优化的BP网络学习算法研究及应用

潘昊,韩小雷

武汉理工大学计算机科学与技术学院，武汉 430070

通讯作者: 潘昊

Abstract

Abstract: A novel BP neural networks learning algorithm based on Particle Swarm Optimiation（PSO） is proposed in this paper.A stochastic global optimization technique is used in this proposed algorithm.Comparing experiment between the proposed algorithm and traditional BP-PSO algorithm，the experiment results show that the proposed algorithm does not only superior to BP algorithm，but also has fast congruence speed，and successful applied in simulating Cement Hydration process.

Key words: Artificial Neural Network, Particle Swarm Optimization, syncretize, cement hydration

摘要： 提出一种新的基于粒子群优化的BP网络学习算法，该算法是一种全局随机优化算法，将该算法与传统BP—PSO算法对比实验表明：提出的算法性能优于BP算法，而且具有良好的收敛性，并成功应用于水泥水化过程仿真。

关键词: 人工神经网络, 粒子群优化算法, 融合, 水泥水化

PAN Hao,HAN Xiao-lei. BP networks training algorithm based on particle swarm optimization[J]. Computer Engineering and Applications, 2008, 44(9): 67-69.

潘昊,韩小雷. 粒子群优化的BP网络学习算法研究及应用[J]. 计算机工程与应用, 2008, 44(9): 67-69.

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BP networks training algorithm based on particle swarm optimization

粒子群优化的BP网络学习算法研究及应用

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