| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 10403564 | IFAC Proceedings Volumes | 2005 | 6 Pages |
Abstract
This paper proposes a new method for prediction of chaotic time series based on Parallel Multi-Layer Perceptron (PMLP) net and dynamics reconstruction technique. The PMLP contains a number of multi-layer perceptron (MLP) subnets connected in parallel. Each MLP subnet predicts the future data independently with a different embedding dimension. The PMLP determines the final predicted result according to the weighted average of all sub-outputs. Simulation results show the effectiveness of the method.
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
Authors
Hongying Yang, Hao Ye, Guizeng Wang, Maiying Zhong,