Predicting citywide crowd flows using deep spatio-temporal residual networks

Junbo Zhang; Yu Zheng; Dekang Qi; Ruiyuan Li; Xiuwen Yi; Tianrui Li

doi:10.1016/j.artint.2018.03.002

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Predicting citywide crowd flows using deep spatio-temporal residual networks

Junbo Zhang Yu Zheng Dekang Qi Ruiyuan Li Xiuwen Yi Tianrui Li

Year: 2018 Journal: Artificial Intelligence Vol: 259 Pages: 147-166 Publisher: Elsevier BV

DOI: 10.1016/j.artint.2018.03.002

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Keywords:

Crowds Computer science Closeness Residual Convolutional neural network Aggregate (composite) Beijing Deep learning Data mining Artificial intelligence Geography Computer security China

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Traffic Prediction and Management Techniques

Physical Sciences → Engineering → Building and Construction

Human Mobility and Location-Based Analysis

Social Sciences → Social Sciences → Transportation

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Predicting citywide crowd flows using deep spatio-temporal residual networks

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