- 1-a Bayesian Time-series Model for Short-term Traffic Flow Forecasting

@inproceedings{Ghosh20081B,
  title={- 1-a Bayesian Time-series Model for Short-term Traffic Flow Forecasting},
  author={Bidisha Ghosh and Biswajit Basu and M. Sinead O’Mahony},
  year={2008}
}
The Seasonal Autoregressive Integrated Moving Average (SARIMA) model is one of the popular univariate time-series models in the field of short-term traffic flow forecasting. The parameters of the SARIMA model are commonly estimated using classical (maximum likelihood estimate and/or least square estimate) methods. In this paper, instead of using classical inference the Bayesian method is employed to estimate the parameters of the SARIMA model considered for modelling. In Bayesian analysis… CONTINUE READING
Highly Cited
This paper has 31 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 20 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 17 references

Analysis of freeway traffic time-series data by using Box–Jenkins techniques

  • M. S. Ahmed, A. R. Cook
  • Transportation Research Record,
  • 1979
Highly Influential
5 Excerpts

Traffic flow forecasting: comparison of modelling approaches

  • B. L. Smith, M. J. Demetsky
  • J. of Transportation Eng.,
  • 1997
Highly Influential
3 Excerpts

Optimized and meta-optimized neural networks for short-term traffic flow prediction: A genetic approach

  • E. I. Vlahogianni, M. G. Karlaftis, J. C. Golias
  • Transport Reviews
  • 2005
2 Excerpts

restoration of images

  • B. Basu, M. M. O’Mahony
  • IEEE Trans. On Pattern Analysis and Machine…
  • 2005

Short-term forecasting: Overview of objectives and methods

  • E. I. Vlahogianni, J. C. Golias, M. G. Karlaftis
  • 2004
2 Excerpts

Short-term freeway traffic flow prediction using a combined neural network model

  • D. H. Lee, W. Z. Zheng, Q. X. Shi
  • Annual Meeting of Transportation Research Board…
  • 2004
2 Excerpts

The Analysis of Time Series: An Introduction, Sixth Edition, Chapman and Hall/CRC, London

  • Chapman, Hall, C. New York. Chatfield
  • Chung, E. and Rosalion,
  • 2004

Urban traffic flow prediction using a fuzzy-neural approach

  • Yin, H.B, S. C. Wong, J. M. Xu, C. K. Wong
  • Transportation Research: Part C,
  • 2002
2 Excerpts

Similar Papers

Loading similar papers…