A Wavelet Neural Network Forecasting Model Based On ARIMA

DOI

10.2991/isccca.2013.68How to use a DOI?

Keywords

ARIMA model,Wavelet Neural Network,time series,BP Neural Network

Abstract

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.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Bin Wang
AU  - Wen-ning Hao
AU  - Gang Chen
AU  - Deng-chao He
AU  - Bo Feng
PY  - 2013/02
DA  - 2013/02
TI  - A Wavelet Neural Network Forecasting Model Based On ARIMA
BT  - Proceedings of the 2nd International Symposium on Computer, Communication, Control and Automation (ISCCCA 2013)
PB  - Atlantis Press
SP  - 277
EP  - 281
SN  - 1951-6851
UR  - https://doi.org/10.2991/isccca.2013.68
DO  - 10.2991/isccca.2013.68
ID  - Wang2013/02
ER  -