Study of predicting combined chaotic time series using neural networks

• Main Authors: WANG, Zhaoxia, Chen, Z.Q., Yuan, Z.Z., Hao, T.Z., Yang, B.H.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2004
• Subjects: Back-propagation (BP) algorithms; Combined chaotic time series; Feed-forward neural networks; Time series prediction; Numerical Analysis and Scientific Computing; OS and Networks
• Online Access: https://ink.library.smu.edu.sg/sis_research/5637
• Institution: Singapore Management University

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) algor...