Global-Local Spatial-Temporal Residual Correlation Network for Urban Traffic Status Prediction

The recent proposed Spatial-Temporal Residual Network (ST-ResNet) model is an effective tool to extract both spatial and temporal characteristics and has been successfully applied to urban traffic status prediction. However, the ST-ResNet model only extracts the local spatial characteristics and ign...

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Detalles Bibliográficos
Autores principales: Bao, Yin-Xin, Cao, Yang, Shen, Qin-Qin, Shi, Quan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8828331/
https://www.ncbi.nlm.nih.gov/pubmed/35154304
http://dx.doi.org/10.1155/2022/7344522

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8828331/
https://www.ncbi.nlm.nih.gov/pubmed/35154304
http://dx.doi.org/10.1155/2022/7344522

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