Chin. Phys. Lett.  2000, Vol. 17 Issue (2): 88-90    DOI:
Original Articles |
Predicting Chaotic Time Series Using Recurrent Neural Network
ZHANG Jia-Shu ;XIAO Xian-Ci
Department of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 610054
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ZHANG Jia-Shu, XIAO Xian-Ci 2000 Chin. Phys. Lett. 17 88-90
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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.
Keywords: 05.45.+b      05.45.Tp      07.05.Mh     
Published: 01 February 2000
PACS:  05.45.+b  
  05.45.Tp (Time series analysis)  
  07.05.Mh (Neural networks, fuzzy logic, artificial intelligence)  
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https://cpl.iphy.ac.cn/       OR      https://cpl.iphy.ac.cn/Y2000/V17/I2/088
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