Citywide Bike Usage Prediction in a Bike-Sharing System

To operate a bike-sharing system efficiently, system operators need to accurately predict how many bikes are to be rented and returned throughout the city. In this paper, we propose a Hierarchical Consistency Prediction (HCP) model to predict the citywide bike usage in the next period. First, an Ada...

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Veröffentlicht in:	IEEE transactions on knowledge and data engineering 2020-06, Vol.32 (6), p.1079-1091
Hauptverfasser:	Li, Yexin, Zheng, Yu
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation models Adaptive algorithms Bicycles Citywide bike usage prediction Clustering Clustering algorithms Gaussian process Gaussian process regressor Linearity Meteorology Prediction algorithms Predictive models Spatio-temporal dataset Time series analysis Urban areas
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