Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection

Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to...

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Detalles Bibliográficos
Autores principales: Yang, Su, Shi, Shixiong, Hu, Xiaobing, Wang, Minjie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4619804/
https://www.ncbi.nlm.nih.gov/pubmed/26496370
http://dx.doi.org/10.1371/journal.pone.0141223

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4619804/
https://www.ncbi.nlm.nih.gov/pubmed/26496370
http://dx.doi.org/10.1371/journal.pone.0141223

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