Spatio-Temporal Residual Graph Attention Network for Traffic Flow Forecasting

• Published in: IEEE internet of things journal p. 1
• Main Authors: Zhang, Qingyong, Li, Changwu, Su, Fuwen, Li, Yuanzheng
• Format: Journal Article
• Language: English
• Published: IEEE 07.02.2023
• Subjects: attention mechanism; Convolution; Convolutional neural networks; Correlation; Feature extraction; Forecasting; graph attention network; Predictive models; Roads; spatio-temporal characteristics; Traffic flow forecasting
• ISSN: 2327-4662
• DOI: 10.1109/JIOT.2023.3243122

Accurate spatio-temporal traffic flow forecasting is significant for the modern traffic management and control. In order to capture the spatio-temporal characteristics of the traffic flow simultaneously, we propose a novel spatio-temporal residual graph attention network (STRGAT). First, the network...