Short-Term Freeway Traffic Flow Prediction: Bayesian Combined Neural Network Approach-Reference-Cited by-同舟云学术

Short-Term Freeway Traffic Flow Prediction: Bayesian Combined Neural Network Approach

Published:2006-02 Issue:2 Volume:132 Page:114-121
ISSN:0733-947X
Container-title:Journal of Transportation Engineering
language:en
Short-container-title:J. Transp. Eng.

Author:

Zheng Weizhong¹²³,Lee Der-Horng¹²³,Shi Qixin¹²³

Affiliation:

1. Research Scholar, Dept. of Civil Engineering, National Univ. of Singapore, 1 Engineering Dr. 2, 117576, Singapore.

2. Associate Professor, Dept. of Civil Engineering, National Univ. of Singapore, 1 Engineering Dr. 2, 117576, Singapore (corresponding author).

3. Professor, Dept. of Civil Engineering, Tsinghua Univ., Beijing, 100084, People’s Republic of China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Transportation,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%290733-947X%282006%29132%3A2%28114%29

Reference19 articles.

1. Ahmed S. A. and Cook A. R. (1979). “Analysis of freeway traffic time-series data using box-Jenkin techniques.” Transportation Research Record 722 Transportation Research Board Washington D.C. 1–9.

2. Cheslow M. Hatcher S. G. and Patel V. M. (1992). “An initial evaluation of alternative intelligent vehicle highway systems architecture.” Rep. No. 92w0000063 MITRE Corporation Bedford Mass.

3. Nonparametric Regression and Short‐Term Freeway Traffic Forecasting

4. The use of neural networks to recognize and predict traffic congestion;Dougherty M. S.;Traffic Eng. Control,1998

5. Short-Term Prediction of Traffic Volume in Urban Arterials

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