Spatial–Temporal Traffic Flow Prediction With Fusion Graph Convolution Network and Enhanced Gated Recurrent Units

Accurately predicting traffic flow is paramount for the efficient operation of transportation systems. The key to enhancing prediction accuracy lies in effectively mining the intricate spatio-temporal correlations within traffic flow data. However, traditional traffic flow prediction methods that co...

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Bibliographic Details

Published in:	IEEE Access
Main Authors:	Chuang Cai, Zhijian Qu, Liqun Ma, Lianfei Yu, Wenbo Liu, Chongguang Ren
Format:	Article
Language:	English
Published:	IEEE 2024-01-01
Subjects:	Traffic flow prediction spatio-temporal correlation gated recurrent unit graph convolution network residual connect
Online Access:	https://ieeexplore.ieee.org/document/10380582/