A3T-GCN: Attention Temporal Graph Convolutional Network for Traffic Forecasting

A3T-GCN: Attention Temporal Graph Convolutional Network for Traffic Forecasting

Accurate real-time traffic forecasting is a core technological problem against the implementation of the intelligent transportation system. However, it remains challenging considering the complex spatial and temporal dependencies among traffic flows. In the spatial dimension, due to the connectivity...

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Bibliographic Details
Main Authors: Jiandong Bai, Jiawei Zhu, Yujiao Song, Ling Zhao, Zhixiang Hou, Ronghua Du, Haifeng Li
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:ISPRS International Journal of Geo-Information
Subjects:
traffic forecasting
attention temporal graph convolutional network
spatial dependence
temporal dependence
Online Access:https://www.mdpi.com/2220-9964/10/7/485

Internet

https://www.mdpi.com/2220-9964/10/7/485

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