Time series prediction using wavelet process neural network

作     者：丁刚 钟诗胜 李洋 

作者机构：School of Mechatronics Engineering Harbin Institute of Technology 

出 版 物：《Chinese Physics B》 (中国物理B（英文版）)

年 卷 期：2008年第17卷第6期

页      面：1998-2003页

核心收录：

学科分类：07[理学] 08[工学] 

基　　金：Project supported by the National Natural Science Foundation of China (Grant No 60572174) the Doctoral Fund of Ministry of Education of China (Grant No 20070213072) the 111 Project (Grant No B07018) the China Postdoctoral Science Foundation (Grant No 20070410264) the Development Program for Outstanding Young Teachers in Harbin Institute of Technology (Grant No HITQNJS.2007.010) 

主　　题：time series prediction wavelet process neural network learning algorithm 

摘      要：In the real world, the inputs of many complicated systems are time-varying functions or processes. In order to predict the outputs of these systems with high speed and accuracy, this paper proposes a time series prediction model based on the wavelet process neural network, and develops the corresponding learning algorithm based on the expansion of the orthogonal basis functions. The effectiveness of the proposed time series prediction model and its learning algorithm is proved by the Macke-Glass time series prediction, and the comparative prediction results indicate that the proposed time series prediction model based on the wavelet process neural network seems to perform well and appears suitable for using as a good tool to predict the highly complex nonlinear time series.