Artificial neural networks in time series forecasting: a comparative analysis

@article{Allende2002ArtificialNN,
  title={Artificial neural networks in time series forecasting: a comparative analysis},
  author={H{\'e}ctor Allende and Claudio Moraga and Rodrigo Salas},
  journal={Kybernetika},
  year={2002},
  volume={38},
  pages={685-707}
}
Artificial neural networks (ANN) have received a great deal of attention in many fields of engineering and science. Inspired by the study of brain architecture, ANN represent a class of non-linear models capable of learning from data. ANN have been applied in many areas where statistical methods are traditionally employed. They have been used in pattern recognition, classification, prediction and process control. The purpose of this paper is to discuss ANN and compare them to non-linear time… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 45 references

Zapranis: Neural model identification, variable selection and model adequacy

  • A P N Referes
  • J. Forecasting
  • 1999

Hristev: Artificial Neural Networks Preprint of a book obtained via Internet from the author

  • Hristev: Artificial Neural Networks Preprint of a…
  • 1998

Ding: Prediction for artificial neural networks

  • J T G Hwang
  • J. Amer. Statist. Assoc
  • 1997

Forecasting in the 1990s

  • C Chatfield
  • Statistician Ą
  • 1997

Lippmann: An introduction to computing with neural nets

  • IEEE ASSP Magazine
  • 1997

Properties of parametric feedforward neural networks

  • C Moraga
  • XXIII Conferencia Latinoamericana de Informatica
  • 1997

Neural networks in applied statistics

  • H S Stern
  • Technometrics
  • 1996

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