| 一种基于粒子群优化算法的神经网络训练方法 |
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| 引用本文： | 秦毅男,廖晓辉,赵庆治.一种基于粒子群优化算法的神经网络训练方法[J].河南师范大学学报(自然科学版),2007,35(3):169-171. |
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| 作者姓名： | 秦毅男 廖晓辉 赵庆治 |
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| 作者单位： | 1. 郑州大学,电气工程学院,郑州,450000
2. 开封市供电公司,河南,开封,475000 |
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| 摘 要： | 介绍了粒子群优化(PSO)算法的原理,研究了将PSO算法应用于神经网络训练的方法,给出了算法软件实现的基本流程,并对Iris分类问题做了仿真实验,通过与BP算法的比较,结果表明基于PSO的神经网络训练算法操作简单,易于实现,而且训练精度较高,有良好的收敛性.
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| 关 键 词： | 粒子群优化 进化算法 神经网络 |
| 文章编号： | 1000-2367（2007）03-0169-03 |
| 修稿时间： | 2006-11-20 |
A Neural Network Training Algorithm Based on Particle Swarm Optimization |
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| QIN Yi-nan,LIAO Xiao-hui,ZHAO Qing-zhi.A Neural Network Training Algorithm Based on Particle Swarm Optimization[J].Journal of Henan Normal University(Natural Science),2007,35(3):169-171. |
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| Authors: | QIN Yi-nan LIAO Xiao-hui ZHAO Qing-zhi |
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| Institution: | 1, College of Electrical Engineering, Zhengzhou University,Zhengzhou 450000, China 2, Kaifeng Power Supply Company, Kaifeng 475000,China |
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| Abstract: | In the paper,the fundamental principles of PSO are introduced firstly.And then,the processes of training neural network by applying PSO algorithm are presented.Simulating experiments of Iris classification problem are also made between proposed algorithm and BP algorithm.A comparison of the two algorithms indicates that the former is a simple one with good convergence. |
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| Keywords: | particle swarm optimization evolutionary algorithm neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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