Chapter
Sep 21, 2015
Traffic Volume Prediction Algorithm Based on Traffic Flow Sequence Partition and a Neural Network
Authors: Jinlong Li [email protected], Jialiang Wu [email protected], and Taomei Gao [email protected]Author Affiliations
Publication: ICTE 2015
Abstract
It is an important premise to identify and predict traffic flow instantly and accurately in ITS. Therefore, it is of great significance to realize the control and induction of ITS. Aiming at the intersection short-term traffic volume forecasting problem, we proposed the combined model prediction algorithm based on the analysis of traffic flow sequence partition and neural network model. This algorithm divides the traffic volume into different patterns along the time and volume dimension by clustering analysis, and then describes and predicts traffic flow value according to different patterns. The experiment results on real data set demonstrate that our algorithm based on the combination model is more accurate.
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Published In
ICTE 2015
Pages: 1504 - 1510
Copyright
© 2015 American Society of Civil Engineers.
History
Published online: Sep 21, 2015
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School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 611756, China. E-mail: [email protected]
School of Civil Engineering, Southwest Jiaotong University, Chengdu 611756, China. E-mail: [email protected]
School of Civil Engineering, Xihua University, Chengdu 611756, China. E-mail: [email protected]
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