A bayesian network approach to time series forecasting of short-term traffic flows

IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC

Volumn , Issue , 2004, Pages 216-221

  Zhang, Changshui ^a   Sun, Shiliang ^a   Yu, Guoqiang ^a  

^a TSINGHUA UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

FORECASTING; INFORMATION ANALYSIS; INTELLIGENT VEHICLE HIGHWAY SYSTEMS; MATHEMATICAL MODELS; OPTIMIZATION; PARAMETER ESTIMATION; PRINCIPAL COMPONENT ANALYSIS; PROBLEM SOLVING; TIME SERIES ANALYSIS; VOICE/DATA COMMUNICATION SYSTEMS;

COMPETITIVE EXPECTATION MAXIMIZATION (CEM); GAUSSIAN MIXTURE MODEL (GMM); INTELLIGENT TRANSPORTATION SYSTEMS (ITS); TRAFFIC MANAGEMENT;

TRAFFIC CONTROL;

EID: 13344295028     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (21)

1. B.M. William, Modeling and Forecasting Vehicular Traffic Flow as a Seasonal Stochastic Time Series Process, Doctoral Dissertation, University of Virginia, Charlottesville, 1999.
2. C.K. Moorthy and B.C. Ratcliffe, Short Term Traffic Forecasting Using Time Series Methods, Transportation planning and technology, Vol. 12, no. 1, 1988.
3. S. Lee and D.B. Fambro, Application of Subsets Autoregressive Integrated Moving Average Model for Short-term Freeway Traffic Volume Forecasting, Transportation Research Record, No. 1678, TRB, National Research Council, Washington, D.C., 1999.
4. I. Okutani and Y.J. Stephanedes, Dynamic Prediction of Traffic Volume through Kalman Filter Theory, Transportation Research, Part B., Vol.18B, 1-11, 1984.
5. T. Edwards, D.S.W. Transley, R.J. Frank, and N. Davey, Traffic Trends Analysis using Neural Networks, http://homepages.feis.herts.ac.uk/~nngroup/pubs/papers/edwards-twannt97.pdf.
6. E.S. Yu and C.Y.R. Chen, "Traffic Prediction Using Neural Networks", Global Telecommunications Conference, 1993, including a Communications Theory Mini-Conference, Technical Program Conference Record, IEEE in Houston, GLOBECOM '93., IEEE , 29 Nov.-2 Dec. 1993, Page(s): 991 -995 vol.2.
7. J. Hall and P. Mars, The Limitations of Artificial Neural Networks for Traffic Prediction; Computers and Communications, 1998, ISCC '98, Proceedings, Third IEEE Symposium on 30 June-2 July 1998, Page(s): 8 -12.
8. G.A. Davis and N.L. Nihan, Non-parametric Regression and Short-term Freeway Traffic Forecasting, Journal of Transportation Engineering, 178-188, 1991.
9. R. Chrobok, J. Wahle, and M. Schreckenberg, "Traffic Forecast using Simulations of Large Scale Networks", IEEE Intelligent Transportation Systems Conference Proceedings, 2001.
10. B.L. Smith and M. Demetsky, Traffic Flow Forecasting: Comparison of Modeling Approaches, Journal of Transportation Engineering, Vol. 123, no. 4, July/Aug, 1997.
11. G.A. Davis, Adaptive Forecasting of Freeway Traffic Congestion, Transportation Research Record, No.1287, TRB, National Research Council, Washing, D.C., 1990.
12. S.C. Chang, R.S. Kim, S.J. Kim, and B.H. Ahn, Traffic-Flow Fore-casting Using a 3-stage model, Proceedings of the IEEE Intelligent Vehicle Symposium 2000, Dearborn (MI), U.S.A., Oct. 3-5, 2000.
13. M.I. Jordan, Learning in Graphical Models, MIT Press, Cambridge, 1999.
14. K.P. Murphy, An Introdcution to Graphical Models, http://www.ai.mit.edu/~murphyk/Papers/intro.gm.pdf, 2001.
15. J.A. Bilmes, A Gentle Tutorial of the EM Algorithm and its Application to Parameter Estimation for Gaussian Mixture and Hidden Markov Models, International Computer Science Institute, Berkeley CA, TR-07-021, Apr., 1998.
16. B.B. Zhang, C.S. Zhang, and X. Yi, Competitive EM Algorithm for Finite Mixture Models, Pattern Recognition, Volume: 37, Issue: 1, January, 2004, pp. 131-144.
17. A.H. Jazwinski, Stochastic Processes and Filtering Theory, Academic Press, Inc., New York and London, 1970.
18. C.R. Rao, Linear Statistical Inference and Its Applications (Second Edition), John Wiley&Sons, Inc., 1973.
19. I.T. Jolliffe, Principal Component Analysis, Springer-Verlag, New York, 1986.
20. R.O. Duda, P.E. Hart, and D.G. Stork, Pattern Classification (Second Edition), Wiley, New York, 2001.
21. J.B. Tenenbaum, V.D. Silva, and J.C. Langford, A Global Geometric Framework for Nonlinear Dimensionality Reduction, Science 290, 2319, 2000.