The Urban Road Short-Term Traffic Flow Prediction Research

Zhen Hai Qin

doi:10.4028/www.scientific.net/AMM.423-426.2954

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 423-426The Urban Road Short-Term Traffic Flow Prediction...

The Urban Road Short-Term Traffic Flow Prediction Research

Abstract:

To predict the future traffic flow status more accurately is of great significance to alleviate urban traffic congestion for a short period of time and avoid the waste of social resources. At first, this paper summarizes the characteristics of urban expressway traffic flow. Then establishes BP neural network short-term traffic flow evaluation model based on MATLAB, and finally through the instance, verify the validity of the model.

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Periodical:

Applied Mechanics and Materials (Volumes 423-426)

Pages:

2954-2956

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.423-426.2954

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Online since:

September 2013

Authors:

Zhen Hai Qin

Keywords:

MATLAB, Neutral Network, Short-Time Transportation Forecast

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References

[1] Dougherty，M．S．，H．R．Kirby，and R．D．Boyl e．The Use of Neural Networks to Recognize and Predict Traffic Congestion．Traffic Engineering and Control，V01．34，No．6, 1993，PP．3ll一314.

Google Scholar

[2] Dianhai Wang. The traffic flow theory [M]. Beijing: people's traffic press, (2001).

Google Scholar

[3] Jianwu Dang, neural network technology and application [M], Beijing: China railway publishing house, (2000).

Google Scholar

[4] Kaili Zhou , Yaogong Kang. Neural network model and MATLAB simulation program design [M]. Beijing: tsinghua university press, (2005).

Google Scholar