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http://dx.doi.org/10.5351/KJAS.2020.36.6.739

Analysis of the Seoul public bikes usage for new rental locations  

Kim, Yesool (Department of Statistics, University of Seoul)
Park, Sion (Department of Statistics, University of Seoul)
Park, Gunwoong (Department of Statistics, University of Seoul)
Publication Information
The Korean Journal of Applied Statistics / v.33, no.6, 2020 , pp. 739-751 More about this Journal
Abstract
Seoul public bike program facilitates access to bicycles and offers potential for greater mobility and health for users. Furthermore, it would have positive impacts on transport congestion, energy use, and the environment. Hence, it is important to find future rental locations by taking to account both bike-demand and regional imbalance. This paper first finds eligible candidates of rental locations with the required spatial conditions such as a sufficient sidewalk width and accessibility of bike pick-up vehicles. And then, estimates public bike daily usage for each selected location via random forest based on Seoul public bike historical usage, Seoul geographical features, regional characteristics, and populations. This study contributes to a better comprehension of the Seoul public bike program, and would be useful in determining new public bike rental locations.
Keywords
new rental location; public bike; public transportation; random forest; usage estimation;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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1 Breimanm, L. (2001). Random forest, Machine Learning, 45, 5-32.   DOI
2 James, G., Witten, D., Hastie, T., and Tibshirani, R. (2013). An Introduction to Statistical Learning: with Applications in R., Springer, New York.
3 Jang, J. M., Gim, T. H. T., and Lee, MY. (2016). A study on the Seoul public bikes use characteristics-a case of the districts of Yeouido and Sangam, Seoul Studies, 17, 77-91.
4 Jung, I. W., Uhm, H. S., and LEE, Y. H. (2018). Demand driven reallocation in bike sharing system, Journal of the Korean Operations Research and Management Science Society, 43, 17-31.   DOI
5 Lee, C. H., Jeong, G. O., and Shin, H. C. (2016). Impace analysis of weather condition and locational characteristics on the usage of public bike sharing system, Journal of Korean Society of Transportation, 34, 394-408.   DOI
6 Lee, E. T. and Son, B. S. (2019). Optimal rebalancing strategy for public bike-sharing system in Seoul, Journal of Korean Society of Transportation, 37, 27-38.   DOI
7 Lee, G. H., Lee, S. G., and Cheon, S. H. (2018). An analysis of locational characteristics and business change in the commercially gentrified residential areas in Seoul, Korea, Journal of the Korean Regional Science Association, 34, 31-47.   DOI
8 Kim, E. M. (2010). Service for bicycle use information based on low carbon green growth, Journal of Korean Society for Geospatial Information Science, 18, 75-81.
9 Kim, D. J., Shin, H. C., Park, J. S., and Im, H. J. (2012). The impact of weather on bicycle usage-focus on usage of bike-sharing system in Goyang, Journal of Transport Research, 19, 77-88.   DOI
10 Yoo, J. E. (2015). Random forest, an alternative data mining technique to decision tree, Journal of Educational Evaluation, 28, 427-448.