A Wavelet Neural Network Forecasting Model Based On ARIMA

摘要：

　　Stock index series is Non-stationary,Nonlinear and factors with impact on stock index fluctuation are complex,a time series forecasting model combined ARIMA model and wavelet neural network is presented.The combined model uses BP neural network as the main framework,uses wavelet basis function instead of transfer function in the network,also add some inner factors of the time series mining by ARIMA model,as the part impute of Wavelet Neural Network.So it is more scientific and rational that using inner factors and external other factors.The last simulate experiment shows that the wavelet neural network forecasting model based on ARIMA has higher accuracy than ARIMA model or BP network.

关键词： ARIMA modei Wavelet Neural Network time series BP Neural Network

作者: Wang Bin Hao Wen-ning Chen Gang He Deng-chao Feng Bo

作者单位: PLA University of Science &Technology Nanjing 210007, China

会议类型: 国际会议

会议名称: 2013 2nd International Symposium on Computer,Communication,Control and Automation(ISCCCA-13)(2013年第二届计算机、通信与自动化国际会议)

会议地点: 太原

会议语种:英文

页码: 277-281

在线出版日期: 2013-04-06（万方平台首次上网日期，不代表论文的发表时间）