(Fanaee-T & Gama, 2014) Bike Sharing Count Prediction Task

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A (Fanaee-T & Gama, 2014) Bike Sharing Count Prediction Task is a fully-supervised univariate point estimation task presented in (Fanaee & Gama, 2014) and supported by a (Fanaee-T & Gama, 2014) Dataset.




  • http://archive.ics.uci.edu/ml/datasets/Bike+Sharing+Dataset
    • Bike sharing systems are new generation of traditional bike rentals wherein the whole process, from membership, rental, to returning the bike back, has become automatic. Through these systems, the user is able to easily rent a bike from a particular position and return it at a different location. Currently, there are about over 500 bike-sharing programs around the world consisting of over 500 thousands bicycles. Today, there exists great interest in these systems due to the important role they have in minimizing traffic, environmental and health issues.

      Apart from the mentioned benefits we get from bike sharing systems, the characteristics of data being generated by these systems also make them attractive for research. Opposed to other transport services such as bus or subway, the duration of travel, and departure and arrival positions are explicitly recorded in these systems. This feature turns bike sharing system into a virtual sensor network that can be used for sensing mobility in the city. Hence, it is expected that most of important events in the city could be detected via monitoring these data.