Short-term traffic flow forecasting using expanded bayesian network for incomplete data

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3174, Issue , 2004, Pages 950-955

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

^a TSINGHUA UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; BAYESIAN NETWORKS; FORECASTING; GAUSSIAN DISTRIBUTION; POLLUTION CONTROL; PROBABILITY DISTRIBUTIONS; TRAFFIC CONTROL;

BAYESIAN NETWORK METHODS; BAYESIAN NETWORK MODELS; CAUSAL RELATIONSHIPS; CAUSE AND EFFECTS; COMPETITIVE EM ALGORITHMS; GAUSSIAN MIXTURE MODEL; JOINT PROBABILITY DISTRIBUTIONS; SHORT-TERM TRAFFIC FLOW FORECASTING;

PRINCIPAL COMPONENT ANALYSIS;

EID: 33745774695     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-28648-6_151     Document Type: Article

References (12)

1. William, B.M.: Modeling and Forecasting Vehicular Traffic Flow as a Seasonal Stochastic Time Series Process. Doctoral dissertation. University of Virginia, Charlottesville (1999)
2. Okutani, I., Stephanedes, Y.J.: Dynamic Prediction of Traffic Volume through Kaiman Filter Theory. Transportation Research, Part B, Vol.lSB (1984) 1-11
3. Edwards, T., Transley, D.S.W., Frank, R.J., Davey, N.: Traffic Trends Analysis using Neural Networks, http://homepages.feis.herts.ac.uk/~nngroup/pubs/ papers/ed-wards-iwannt97.pdf (1997)
4. Davis, G.A., Nihan, N.L.: Non-Parametric Regression and Short-Term Freeway Traffic Forecasting. Journal of Transportation Engineering (1991) 178-188
5. Roland, C., Joachim, W., Michael, S.: Traffic Forecast Using Simulations of Large Scale Networks. IEEE Intelligent Transportation Systems Conference Proceedings (2001)
6. Davis, G.A.: Adaptive Forecasting of Freeway Traffic Congestion. Transportation Research Record, No.1287. TRB, National Research Council, Washing, D.C. (1990)
7. Kevin, P.M.: An Introduction to Graphical Models. http://www.ai.mit.edu/ ~murphyk/Papers/intro.gm.pdf (2001)
8. Jolliffe, I.T.: Principal Component Analysis. Springer-Verlag, New York (1986)
9. Jeff, A.B.: 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 (1998)
10. Zhang, B.B., Zhang, C.S., Yi, X.: Competitive EM Algorithm for Finite Mixture Models. Pattern Recognition, Volume: 37, Issue: 1, January (2004) 131-144
11. Andrew, H.J.: Stochastic Processes and Filtering Theory . Academic Press, Inc., New York and London (1970)
12. Rao, C.R.: Linear Statistical Inference and Its Applications (Second Edition). John Wiley & Sons, Inc. (1973)