Long-term time series prediction with the NARX network: An empirical evaluation

@article{Menezes2008LongtermTS,
  title={Long-term time series prediction with the NARX network: An empirical evaluation},
  author={Jos{\'e} Maria P. Menezes and Guilherme De A. Barreto},
  journal={Neurocomputing},
  year={2008},
  volume={71},
  pages={3335-3343}
}
The NARX network is a dynamical neural architecture commonly used for input–output modeling of nonlinear dynamical systems. When applied to time series prediction, the NARX network is designed as a feedforward time delay neural network (TDNN), i.e., without the feedback loop of delayed outputs, reducing substantially its predictive performance. In this paper, we show that the original architecture of the NARX network can be easily and efficiently applied to long-term (multi-step-ahead… CONTINUE READING
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A Field Guide to Dynamical Recurrent Networks

  • J. F. Kolen, S. C. Kremer
  • Wiley, IEEE Press, New York
  • 2001
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