A Pmlp Based Method for Chaotic Time Series Prediction

نویسندگان

  • Hongying Yang
  • Hao Ye
  • Guizeng Wang
  • Maiying Zhong
چکیده

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. Copyright © 2005 IFAC

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تاریخ انتشار 2005