Long Short-Term Fusion Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting

Long Short-Term Fusion Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting

Traffic flow forecasting, as one of the important components of intelligent transport systems (ITS), plays an indispensable role in a wide range of applications such as traffic management and city planning. However, complex spatial dependencies and dynamic changes in temporal patterns exist between...

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Bibliographic Details
Main Authors: Hui Zeng, Chaojie Jiang, Yuanchun Lan, Xiaohui Huang, Junyang Wang, Xinhua Yuan
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Electronics
Subjects:
long short-term spatial-temporal dependencies
spatial-temporal graph convolution
traffic flow forecasting
Online Access:https://www.mdpi.com/2079-9292/12/1/238

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https://www.mdpi.com/2079-9292/12/1/238

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