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Traffic prediction in a bike-sharing system
2015
Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems - GIS '15
Bike-sharing systems are widely deployed in many major cities, providing a convenient transportation mode for citizens' commutes. As the rents/returns of bikes at different stations in different periods are unbalanced, the bikes in a system need to be rebalanced frequently. Real-time monitoring cannot tackle this problem well as it takes too much time to reallocate the bikes after an imbalance has occurred. In this paper, we propose a hierarchical prediction model to predict the number of bikes
doi:10.1145/2820783.2820837
dblp:conf/gis/LiZZC15
fatcat:ps6z7usmvfht5ncovw7eebjcsm