Chapter
Aug 12, 2020
A Short-Term Traffic Flow Combination Prediction Model with Adaptive Weights
Authors: Chuanxia Sun [email protected], Xiaoliang Sun [email protected], Peixuan Yin [email protected], and Shenyuan Zhang [email protected]Author Affiliations
Publication: CICTP 2020
ABSTRACT
A time-varying weighted combination model is proposed to predict the short-term traffic flow in the paper. The changed weights will much minimize the influence of random factors and generalize the application conditions. Firstly, the training data are classified into several categories according to the traffic situations, and LS-SVM is used to train the single local prediction model of each category; Secondly, the occurring possibility of different traffic situations is made as the weight of the corresponding local prediction model; and then the model is constructed with the linear weighted combination strategy. Finally, the experiment with the actual speed data shows that the method is effective.
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Published In
CICTP 2020
Pages: 324 - 331
Copyright
© 2020 American Society of Civil Engineers.
History
Published online: Aug 12, 2020
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Authors
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1Highway Administration Bureau, Henan Provincial Dept. of Transportation, Zhengzhou 450016, China. Email: [email protected]
2Research Institute of Highway, Ministry of Transport, Beijing 10088, China. Email: [email protected]
3Highway Administration Bureau, Henan Provincial Dept. of Transportation, Zhengzhou 450016, China; Email: [email protected]
4Highway Administration Bureau, Henan Provincial Dept. of Transportation, Zhengzhou 450016, China. Email: [email protected]
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