Prediction of Urban Taxi Travel Demand by Using Hybrid Dynamic Graph Convolutional Network Model

The efficient and accurate prediction of urban travel demand, which is a hot topic in intelligent transportation research, is challenging due to its complicated spatial-temporal dependencies, dynamic nature, and uneven distribution. Most existing forecasting methods merely considered the static spat...

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Detalles Bibliográficos
Autores principales: Zhao, Jinbao, Kong, Weichao, Zhou, Meng, Zhou, Tianwei, Xu, Yuejuan, Li, Mingxing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9415392/
https://www.ncbi.nlm.nih.gov/pubmed/36015740
http://dx.doi.org/10.3390/s22165982

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9415392/
https://www.ncbi.nlm.nih.gov/pubmed/36015740
http://dx.doi.org/10.3390/s22165982

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