Study of predicting combined chaotic time series using neural networks

Author

Zhaoxia WANG, Singapore Management UniversityFollow
Z.Q. Chen
Z.Z. Yuan
T.Z. Hao
B.H. Yang

Publication Type

Journal Article

Publication Date

10-2004

Abstract

The combined chaotic time series is predicted by using the standard feed-forward neural networks (NN). Henon and Lozi systems are used to generate the combined chaotic time series. From the forecasting results, it can be concluded that the NN, which is trained by improved back-propagation (BP) algorithms, can be well applicable for combined chaotic time series prediction.

Keywords

Back-propagation (BP) algorithms, Combined chaotic time series, Feed-forward neural networks, Time series prediction

Discipline

Numerical Analysis and Scientific Computing | OS and Networks

Research Areas

Intelligent Systems and Optimization

Publication

Guangdianzi Jiguang / Journal of Optoelectronics Laser

Volume

15

Issue

10

First Page

1225

Last Page

1228

ISSN

1005-0086

Citation

WANG, Zhaoxia; Chen, Z.Q.; Yuan, Z.Z.; Hao, T.Z.; and Yang, B.H.. Study of predicting combined chaotic time series using neural networks. (2004). Guangdianzi Jiguang / Journal of Optoelectronics Laser. 15, (10), 1225-1228.
Available at: https://ink.library.smu.edu.sg/sis_research/5637