Forecasting the exchange rate using the improved SAPSO neural network

被引：1

作者：

Meng Li ^{[1
]}

Dong Lijun ^{[1
]}

机构：

[1] Xiamen Univ, Sch Management, Xiamen 361005, Peoples R China

来源：

AUTOMATION EQUIPMENT AND SYSTEMS, PTS 1-4 | 2012年 / 468-471卷

关键词：

simulated annealing particle swarm optimization; PSO; simulated annealing; exchange rate forecasts;

D O I：

10.4028/www.scientific.net/AMR.468-471.1714

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The paper researches on the behavior of particles in the PSO, and improves the situation of easily falling into local optimum by the right combination of simulated annealing and PSO. In the paper, the author compared the original PSO and the improved SAPSO algorithms in neural network training. The empirical research shows that the improved algorithm performed better than the PSO algorithm in global search ability, and the prediction accuracy is greatly increased.

引用

页码：1714 / 1720

页数：7

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