,Time series prediction using wavelet process neural network

• 作 者: Ding Gang Zhong Shi-Sheng Li Yang
• 机 构: School of Mechatronics Engineering, Harbin Institute of Technology, Harbin,150001, China
• 出 处: 中国物理B(英文版)
• 发表日期: 2008年6期
• 关键词: time series prediction wavelet process neural network learning algorithm

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 leaing algorithm based on the expansion of the orthogonal basis functions. The effectiveness of the proposed time series prediction model and its leaing algorithm is proved by the Mackey-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.