STSGAN: Spatial-Temporal Global Semantic Graph Attention Convolution Networks for Urban Flow Prediction

STSGAN: Spatial-Temporal Global Semantic Graph Attention Convolution Networks for Urban Flow Prediction

Accurate urban traffic flow prediction plays a vital role in Intelligent Transportation System (ITS). The complex long-term and long-range spatiotemporal correlations of traffic flow pose a significant challenge to the prediction task. Most current research methods focus only on spatial correlations...

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Bibliographic Details
Main Authors:	Junwei Zhou, Xizhong Qin, Kun Yu, Zhenhong Jia, Yan Du
Format:	Article
Language:	English
Published:	MDPI AG 2022-07-01
Series:	ISPRS International Journal of Geo-Information
Subjects:	traffic flow prediction spatial–temporal modeling graph convolutional network attention mechanism
Online Access:	https://www.mdpi.com/2220-9964/11/7/381

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