A MULTI RESOLUTION FORECASTING METHOD FOR SHORT LENGTH TIME SERIES DATA USING NEURAL NETWORKS

S. Arash Sheikholeslam, Pouya Bidram

Abstract

In this paper a new multi-resolution approach for time series forecasting based on a composition of three different types of neural networks is introduced and developed. A comparison between this method and 3 ordinary neural network based forecasting methods is obtained experimentally.

References

  1. I. Daubechies, Ten Lectures on Wavelets, Vol. 61 of Proc. CBMS-NSF Regional Conference Series in Applied Mathematics. Philadelphia, PA: SIAM (1992).
  2. MT Hagan, HB Demuth, Neural network design, PWS Publishing Company, Thomson Learning (1996).
  3. S. Haykin. Neural Networks: A Comprehensive Foundation (2nd Editioned.), Prentice-Hall, Upper Saddle River, NJ (1999).
  4. S. Mallat. A Wavelet Tour of Signal Processing, Academic Press, San Diego (1998).
  5. Peter J. Brockwell and Richard A. Davis, Introduction to Time Series and Forecasting, Springer, New York (1996).
  6. C. BURRUS, A. SIDNEY RAMESH and H. GUO. Introduction to Wavelets and Wavelet Transforms: A primer, Prentice-Hall PTR (1998).
  7. G. Dreyfus, Neural Networks, Methodology and Applications, Springer (2005).
  8. DP Mandic, JA Chambers, Recurrent neural networks for prediction: learning algorithms, architectures, and stability, Wiley (2001)
  9. Emad W. Saad, Danil V. Prokhorov, Danold C. Wunsch, comparative Study of Stock Trend Prediction Using Time Delay, Recurrent and Probabilistic Neural Networks, IEEE transaction on neural networks (1998).
  10. R. A. Aliev,B. Fazlollahi, R. R. Aliev, B. Guirimov, Linguistic time series forcasting using fuzzy recurrent neural network, Springer - verlog (2007).
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Paper Citation


in Harvard Style

Arash Sheikholeslam S. and Bidram P. (2010). A MULTI RESOLUTION FORECASTING METHOD FOR SHORT LENGTH TIME SERIES DATA USING NEURAL NETWORKS . In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-674-021-4, pages 532-535. DOI: 10.5220/0002714305320535


in Bibtex Style

@conference{icaart10,
author={S. Arash Sheikholeslam and Pouya Bidram},
title={A MULTI RESOLUTION FORECASTING METHOD FOR SHORT LENGTH TIME SERIES DATA USING NEURAL NETWORKS},
booktitle={Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2010},
pages={532-535},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002714305320535},
isbn={978-989-674-021-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - A MULTI RESOLUTION FORECASTING METHOD FOR SHORT LENGTH TIME SERIES DATA USING NEURAL NETWORKS
SN - 978-989-674-021-4
AU - Arash Sheikholeslam S.
AU - Bidram P.
PY - 2010
SP - 532
EP - 535
DO - 10.5220/0002714305320535