Influence of Noise to Chaotic Time Series Prediction in Environment

Article Preview

Abstract:

When constructing chaotic time series prediction model involving noise, noise would influence the chaotic characteristics of the time series and lower the precision and generalization ability of the model. This paper applies wavelet transform to make de-noise on gas emission time series. It uses state space reconstruction theory to determine the embedding dimension and delay time. In the constructed phase space, build BP artificial neural network model to make prediction. Prediction model constructed after wavelet de-noises achieves good prediction performance.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

896-900

Citation:

Online since:

July 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Ge Zhe-xue, Sha Wei . Wavelet theory and MATLAB R2007 realization. Beijing: electronic publishing house, (2007).

Google Scholar

[2] Sivakumar B. Chaos theory in geophysics: past, present and future. Chaos solution & Fractals, 2004, 19: 441-462.

DOI: 10.1016/s0960-0779(03)00055-9

Google Scholar

[3] Galka A, Maa B T, Pfister G. Estimating the dimension of high-dimensional attraetors: a comparison between two algorithms. Physica D, 1998, 121(3-4): 237-251.

DOI: 10.1016/s0167-2789(98)00168-7

Google Scholar

[4] HAN Min. chaotic time series prediction theory and methods . Beijing: China water conservancy publishing house, (2007).

Google Scholar