Stock index prediction based on the PSOPI-BP neural network

被引：0

作者：

Cheng, Jun ^{[1
,2
]}

Li, Rongjun ^{[2
]}

Deng, Xue ^{[3
]}

机构：

[1] Guangzhou Maritime Institute, Guangzhou

[2] School of Business Administration, South China University of Technology, Guangzhou

[3] Department of Mathematics, School of Science, South China University of Technology, Guangzhou

来源：

Journal of Information and Computational Science | 2014年 / 11卷 / 13期

关键词：

Neural network; Prediction; PSO; Stock index;

D O I：

10.12733/jics20104402

中图分类号：

学科分类号：

摘要：

In order to improve the prediction ability of the Neuron Network in stock index prediction, we proposed an improve particle swarm neural network algorithm. The Particle Swarm Optimization algorithm based on Parasitic Immune (PSOPI) was used to optimize combination weights of BP neural network model parameters. The BP algorithm was also to obtain the parameters of network further accurate. Finally, experimental results demonstrate the efficacy of our improved algorithm. Copyright © 2014 Binary Information Press.

引用

页码：4837 / 4844

页数：7

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