粒子群优化的BP网络学习算法研究及应用  

BP networks training algorithm based on particle swarm optimization

作　　者：潘昊[1] 韩小雷[1] 

机构地区：[1]武汉理工大学计算机科学与技术学院,武汉430070

出　　处：《计算机工程与应用》2008年第9期67-69,共3页Computer Engineering and Applications

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。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.

关 键 词：人工神经网络 粒子群优化算法 融合 水泥水化 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]