Forecasting traffic flow with spatial–temporal convolutional graph attention networks

Xiyue Zhang; Yong Xu; Yizhen Shao

doi:10.1007/s00521-022-07235-z

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JOURNAL ARTICLE

Forecasting traffic flow with spatial–temporal convolutional graph attention networks

Xiyue Zhang Yong Xu Yizhen Shao

Year: 2022 Journal: Neural Computing and Applications Vol: 34 (18)Pages: 15457-15479 Publisher: Springer Science+Business Media

DOI: 10.1007/s00521-022-07235-z

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Keywords:

Computer science Graph Convolutional neural network Data mining Residual Semantics (computer science) Traffic congestion Artificial intelligence Theoretical computer science Algorithm

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4.19

FWCI (Field Weighted Citation Impact)

Refs

0.93

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Is in top 1%

Is in top 10%

Citation History

Topics

Traffic Prediction and Management Techniques

Physical Sciences → Engineering → Building and Construction

Traffic control and management

Physical Sciences → Engineering → Control and Systems Engineering

Transportation Planning and Optimization

Social Sciences → Social Sciences → Transportation

Forecasting traffic flow with spatial–temporal convolutional graph attention networks

Metrics

Citation History

Topics

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