Predicting Chaotic Time Series Using Recurrent Neural Network
-
Abstract
A new proposed method, i.e. the recurrent neural network (RNN), is introduced to predict chaotic time series. The effectiveness of using RNN for making one-step and multi-step predictions is tested based on remarkable few datum points by computer-generated chaotic time series. Numerical results show that the RNN proposed here is a very powerful tool for making prediction of chaotic time series.
Article Text
-
-
-
About This Article
Cite this article:
ZHANG Jia-Shu, XIAO Xian-Ci. Predicting Chaotic Time Series Using Recurrent Neural Network[J]. Chin. Phys. Lett., 2000, 17(2): 88-90.
ZHANG Jia-Shu, XIAO Xian-Ci. Predicting Chaotic Time Series Using Recurrent Neural Network[J]. Chin. Phys. Lett., 2000, 17(2): 88-90.
|
ZHANG Jia-Shu, XIAO Xian-Ci. Predicting Chaotic Time Series Using Recurrent Neural Network[J]. Chin. Phys. Lett., 2000, 17(2): 88-90.
ZHANG Jia-Shu, XIAO Xian-Ci. Predicting Chaotic Time Series Using Recurrent Neural Network[J]. Chin. Phys. Lett., 2000, 17(2): 88-90.
|