计算机工程与应用Issue(8)：160-163,197,5.DOI:10.3778/j.issn.1002-8331.1204-0435
基于差分进化的BP神经网络预测混沌时间序列
Prediction for chaotic time series of BP neural network based on differential evolution
摘要
Abstract
A prediction method for chaotic time series of BP neural based on DE is proposed to overcome the problems such as long computing time and easy to fall into local minimum by incorporating Differential Evolution(DE)and neural network. DE is used to optimize the weights and thresholds of BP neural network, and the BP neural network is used to search for the optimal solution. The efficiency of the proposed prediction method is tested by the simulation of three typical nonlinear systems, and the precision of this algorithm is compared with BP algorithms. The simulation results show that the proposed method has better nonlinear fitting ability and higher forecasting accuracy.关键词
混沌时间序列/反向传播(BP)神经网络/差分进化/预测Key words
chaotic time series/Back Propagation(BP)neural/Differential Evolution(DE)/prediction分类
信息技术与安全科学引用本文复制引用
邬月春,王铁君..基于差分进化的BP神经网络预测混沌时间序列[J].计算机工程与应用,2013,(8):160-163,197,5.基金项目
甘肃省教育厅科研项目(No.1118B-03) （No.1118B-03）
甘肃省自然科学基金(No.1112RJZA051) （No.1112RJZA051）
