@article{VOGEL2011514,
title = {Understanding Bike-Sharing Systems using Data Mining: Exploring Activity Patterns},
journal = {Procedia - Social and Behavioral Sciences},
volume = {20},
pages = {514-523},
year = {2011},
note = {The State of the Art in the European Quantitative Oriented Transportation and Logistics Research – 14th Euro Working Group on Transportation & 26th Mini Euro Conference & 1st European Scientific Conference on Air Transport},
issn = {1877-0428},
doi = {https://doi.org/10.1016/j.sbspro.2011.08.058},
url = {https://www.sciencedirect.com/science/article/pii/S1877042811014388},
author = {Patrick Vogel and Torsten Greiser and Dirk Christian Mattfeld},
keywords = {Bike-Sharing, Data Mining, Activity Patterns},
abstract = {In this paper we analyze extensive operational data from bike-sharing systems in order to derive bike activity patterns. A common issue observed in bike-sharing systems is imbalances in the distribution of bikes. We use Data Mining to gain insight into the complex bike activity patterns at stations. Activity patterns reveal imbalances in the distribution of bikes and lead to a better understanding of the system structure. A structured Data Mining process supports planning and operating decisions for the design and management of bike-sharing systems.}
}