Paper Title:
Research on the Magnitude Time Series Prediction Based on Wavelet Neural Network
  Abstract

Based on the fundamental principles of the wavelet analysis combining with BP neural network, the paper can obtain the minimum embedding dimension and delay time. According to the chaos theory, the phase space of the magnitude time series can be reconstructed by Takens theorem. The paper uses wavelet neural network to train and test the nonlinear magnitude time series in the reconstructed phase space. The simulation results show that the predictive effect of the magnitude time series is remarkable and the predictive performance of single-step prediction is superior to that of multi-step prediction.

  Info
Periodical
Chapter
Chapter 1: Mechanic Manufacturing System and Automation
Edited by
Zhixiang Hou
Pages
233-236
DOI
10.4028/www.scientific.net/AMM.128-129.233
Citation
Y. L. Chen, Y. Chen, Q. Huang, "Research on the Magnitude Time Series Prediction Based on Wavelet Neural Network", Applied Mechanics and Materials, Vols. 128-129, pp. 233-236, 2012
Online since
October 2011
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Price
$32.00
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