Understanding Bike-Sharing Systems using Data Mining: Exploring Activity Patterns

By Patrick Vogel, T. Greiser, D. Mattfeld. 2011

333 citations recorded by the source corpus.

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.

Subfields: Transportation

View Paper: https://www.semanticscholar.org/paper/b78f3611f90091fd7ee764049e21069ed8bd173f

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In Transportation

1. Hadi Fanaee-T
2. João Gama

Citations in the corpus

• Event labeling combining ensemble detectors and background knowledge (2014, background): “Some few researches have already addressed bike sharing data analysis [6,51] mostly via spatiotemporal analysis to aid operation-oriented decisions.”