Dynamic Spatio-Temporal Graph-Based CNNs for Traffic Flow Prediction

Dynamic Spatio-Temporal Graph-Based CNNs for Traffic Flow Prediction

Forecasting future traffic flows from previous ones is a challenging problem because of their complex and dynamic nature of spatio-temporal structures. Most existing graph-based CNNs attempt to capture the static relations while largely neglecting the dynamics underlying sequential data. In this art...

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Bibliographic Details
Main Authors: Ken Chen, Fei Chen, Baisheng Lai, Zhongming Jin, Yong Liu, Kai Li, Long Wei, Pengfei Wang, Yandong Tang, Jianqiang Huang, Xian-Sheng Hua
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Graph neural networks
spatio-temporal graph
convolutional neural network
traffic forecasting
time series regression
Online Access:https://ieeexplore.ieee.org/document/9207934/

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