Multicomponent Spatial-Temporal Graph Attention Convolution Networks for Traffic Prediction with Spatially Sparse Data

Predicting traffic data on traffic networks is essential to transportation management. It is a challenging task due to the complicated spatial-temporal dependency. The latest studies mainly focus on capturing temporal and spatial dependencies with spatially dense traffic data. However, when traffic...

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Detalles Bibliográficos
Autores principales: Liu, Shaohua, Dai, Shijun, Sun, Jingkai, Mao, Tianlu, Zhao, Junsuo, Zhang, Heng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8718320/
https://www.ncbi.nlm.nih.gov/pubmed/34976047
http://dx.doi.org/10.1155/2021/9134942

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8718320/
https://www.ncbi.nlm.nih.gov/pubmed/34976047
http://dx.doi.org/10.1155/2021/9134942

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