Research on the Application of Intelligent Algorithm in Short-Term Traffic Flow Forecast

DOI

10.2991/amcce-15.2015.50How to use a DOI?

Keywords

Short-term traffic flow prediction; genetic algorithm

Abstract

In recent years, with the vigorous development of intelligent transportation systems, traffic control and traffic flow guidance have become popular issue of intelligent transportation systems (ITS). The key issue to achieve traffic control guidance is to realize real-time and accurate short-term traffic flow forecasting. And the accuracy and real-time of prediction directly impact traffic control and induced effect. Achieving an accurate prediction of urban road short-term traffic flow is the key of urban road traffic control and traffic guidance. Since the single prediction method for the current is of low precision, we proposed wavelet and support vector machine (SVM) method to predict new fusion; in order to avoid falling into local optimal problem in the process while learning SVM knowledge, we use the particle swarm optimization (PSO) to optimize the key parameters of SVM and in order to improve the prediction accuracy of short-term traffic flow.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Danping Wang
AU  - Kunyuan Hu
AU  - Xiaowei Han
PY  - 2015/04
DA  - 2015/04
TI  - Research on the Application of Intelligent Algorithm in Short-Term Traffic Flow Forecast
BT  - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering
PB  - Atlantis Press
SP  - 277
EP  - 282
SN  - 1951-6851
UR  - https://doi.org/10.2991/amcce-15.2015.50
DO  - 10.2991/amcce-15.2015.50
ID  - Wang2015/04
ER  -