The Research of Neural Network Based on Hybrid Particle Swarm Optimization

TIAN Yu-bo; PAN Peng-peng

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The Research of Neural Network Based on Hybrid Particle Swarm Optimization

更新时间：2026-09-04

- The Research of Neural Network Based on Hybrid Particle Swarm Optimization
- Vol. 28, Issue 6, Pages: 156-159(2011)
- 作者机构：
  
  江苏科技大学机构电子信息学院,江苏,镇江,212003
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2011
- 稿件说明：
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田雨波, 潘朋朋. 混合粒子群算法优化神经网络的研究[J]. 微电子学与计算机, 2011, 28(6): 156-159.

TIAN Yu-bo, PAN Peng-peng. The Research of Neural Network Based on Hybrid Particle Swarm Optimization[J]. 2011, 28(6): 156-159.
田雨波, 潘朋朋. 混合粒子群算法优化神经网络的研究[J]. 微电子学与计算机, 2011, 28(6): 156-159. DOI：

TIAN Yu-bo, PAN Peng-peng. The Research of Neural Network Based on Hybrid Particle Swarm Optimization[J]. 2011, 28(6): 156-159. DOI：

摘要

针对BP神经网络初始权阈值的确定所具有的随机性和各个隐含层神经元数的不确定性

通过利用混合粒子群优化算法来同时优化神经网络的初始权阈值和结构.首先通过混合粒子群优化算法来确定一个较好的搜索空间

然后在这个解空间里再通过BP算法对网络进行训练和学习

搜索出最优的网络结构和权阈值.通过Iris模式分类、Wine模式分类问题和广义异或问题来对该模型进行训练和测试

相比遗传算法等其他算法

该模型可以获得更高的正确识别率

结果表明此方法是可行的.

Abstract

Aiming at the random of the determination of initial weight and the number of neurons of the hidden layers for BP neural network

this paper utilizes hybrid particle swarm optimization to optimize the initial weight and structure for the neural network.It is used to get a better search space by hybrid particle swarm optimization firstly

and then the network is trained and learned in the solution space by BP.Thereby

it searches out the optimal network structure and weight.This model is used to train and test by the use of Iris pattern classification

Wine pattern classification and generalized XOR problem

compared with other algorithm such as genetic algorithm

it can get higher recognition rate.The result shows that the way of this paper is feasible.

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Related Author

LIN Qian-yu

MA Bin

CHEN Hang

Related Institution

Chengyi University College, Jimei University

1 Department of Information Science and Technology, Shandong University of Political Science and Law

2 Key Laboratory of Forensic Evidence in Shandong Province(Shandong University of Political Science and Law)

3 School of Electrical Engineering, Shandong University

Department of Computer, Tianhe College of Guangdong Polytechnic Normal University

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