Predicting Chaotic Time Series Using Recurrent Neural Network
| Autor: | Jia-Shu Zhang, Xian-Ci Xiao |
|---|---|
| Rok vydání: | 2000 |
| Předmět: |
Nonlinear Sciences::Chaotic Dynamics
Nonlinear Sciences::Adaptation and Self-Organizing Systems Recurrent neural network Series (mathematics) Computer science ComputerSystemsOrganization_MISCELLANEOUS Computer Science::Neural and Evolutionary Computation Chaotic General Physics and Astronomy Geodetic datum Algorithm |
| Zdroj: | Chinese Physics Letters. 17:88-90 |
| ISSN: | 1741-3540 0256-307X |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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