Spatiotemporal Adaptive Fusion Graph Network for Short-Term Traffic Flow Forecasting

Spatiotemporal Adaptive Fusion Graph Network for Short-Term Traffic Flow Forecasting

Traffic flow forecasting is challenging for us to analyze intricate spatial–temporal dependencies and obtain incomplete information of spatial–temporal connection. Existing frameworks mostly construct spatial and temporal modeling based on a fixed graph structure and given time series. However, a fi...

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Bibliographic Details
Main Authors: Shumin Yang, Huaying Li, Yu Luo, Junchao Li, Youyi Song, Teng Zhou
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Mathematics
Subjects:
intelligent transportation system
traffic flow modeling
time series analysis
deep learning
noise-immune learning
Online Access:https://www.mdpi.com/2227-7390/10/9/1594

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https://www.mdpi.com/2227-7390/10/9/1594

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