计算机应用与软件2016，Vol.33Issue(10)：284-287,4.DOI:10.3969/j.issn.1000-386x.2016.10.063
基于经验模态分解的小波神经网络预测模型
WAVELET NEURAL NETWORK PREDICTION MODEL BASED ON EMPIRICAL MODEL DECOMPOSITION
张彦霞 1肖清泰 1徐建新 2桑秀丽1
作者信息
- 1. 昆明理工大学质量发展研究院 云南 昆明 650093
- 2. 昆明理工大学省部共建复杂有色金属资源清洁利用国家重点实验室 云南 昆明 650093
- 折叠
摘要
Abstract
Wavelet neural network (WNN)can’t achieve adaptive multi-resolution analysis on non-stationary and nonlinear time series prediction,and its prediction accuracy needs to be improved.In order to solve the problems above,this paper proposes an EMD-based prediction model of wavelet neural network.First,it applies empirical mode decomposition (EMD)on non-linear and non-stationary time series so as to reduce the non-stationarity of time series.Then,it builds respectively the WNN models of intrinsic mode functions (IMF)and remainders derived from EMD analysis.Finally,it summarises the results of each prediction to obtain the final forecasting value.Through data verification,it is proved that the prediction accuracy of new model is higher than that of BP neural network and WNN.关键词
经验模态分解/小波神经网络/BP神经网络/预测Key words
Empirical mode decomposition/Wavelet neural networks/Back propagation neural network/Forecasting分类
信息技术与安全科学引用本文复制引用
张彦霞,肖清泰,徐建新,桑秀丽..基于经验模态分解的小波神经网络预测模型[J].计算机应用与软件,2016,33(10):284-287,4.
