Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction

This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dim...

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Detalles Bibliográficos
Autores principales: Ma, Xiaolei, Dai, Zhuang, He, Zhengbing, Ma, Jihui, Wang, Yong, Wang, Yunpeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5422179/
https://www.ncbi.nlm.nih.gov/pubmed/28394270
http://dx.doi.org/10.3390/s17040818

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5422179/
https://www.ncbi.nlm.nih.gov/pubmed/28394270
http://dx.doi.org/10.3390/s17040818

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