计算机应用与软件Issue(2)：276-279,4.DOI:10.3969/j.issn.1000-386x.2016.02.064
基于布谷鸟算法优化 BP 神经网络模型的股价预测
STOCK FORECASTING MODEL BASED ON OPTIMISING BP NEURAL NETWORK WITH CUCKOO SEARCH
孙晨 1李阳 2李晓戈 1于娇艳3
作者信息
- 1. 西安邮电大学计算机学院 陕西 西安 710100
- 2. 北京交通大学电子信息工程学院 北京 100044
- 3. 西安外国语大学英文学院 陕西 西安 710100
- 折叠
摘要
Abstract
This paper puts forward the method of predicting the stock market by using the cuckoo search algorithm to optimise BP-neural network(CS-BP)aimed at the problem of current intelligent algorithms in poor prediction accuracy on the market.Besides,it compares its test result with the results of PSO-BP model (optimising BP-neural network with particle swarm optimisation)and GA-BP model (optimising BP-neural network with genetic algorithm).After analysing the data backtesting result of the closing price of daily candlesticks of SZ300091 (JTL),we can conclude that the CS-BP model is obviously superior to these two algorithms,it can effectively predict the stock market with about 98.633% of accuracy for thirty days prediction.关键词
布谷鸟算法/神经网络/股票/预测Key words
CS algorithm/Neural network/Stock/Prediction分类
信息技术与安全科学引用本文复制引用
孙晨,李阳,李晓戈,于娇艳..基于布谷鸟算法优化 BP 神经网络模型的股价预测[J].计算机应用与软件,2016,(2):276-279,4.
