Hybrid cluster-regression approach to model bikeshare station usage
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ML studies help understand how usage patterns for bike stations depend on their immediate urban surroundings.
“ML studies help to understand how usage patterns for bike stations depend on their immediate urban surroundings [364].”
From Tackling climate change with machine learning (2023) · cites this paper as [364]
Cites
Jain, A. K., Murty, M. N., & Flynn, P. J. (1999) · ACM Computing Surveys · doi:10.1145/331499.331504 · Cited by 13,532 · see citing works
FCM: The fuzzy c-means clustering algorithm
Bezdek, J. C., Ehrlich, R., & Full, W. E. (1984) · Computers & Geosciences · doi:10.1016/0098-3004(84)90020-7 · Cited by 6,706 · see citing works
Bikesharing in Europe, the Americas, and Asia
Shaheen, S., Guzman, S., & Hua, Z. (2010) · Transportation Research Record Journal of the Transportation Research Board · doi:10.3141/2143-20 · Cited by 1,152 · see citing works
Bike-sharing: History, Impacts, Models of Provision, and Future
DeMaio, P. (2009) · Journal of Public Transportation · doi:10.5038/2375-0901.12.4.3 · Cited by 1,081 · see citing works
Sensitivity and specificity of information criteria
(2019) · doi:10.1093/bib/bbz016 · Cited by 718 · see citing works
Bike Share: A Synthesis of the Literature
Fishman, E. K., Washington, S. P., & Haworth, N. L. (2013) · Transport Reviews · doi:10.1080/01441647.2013.775612 · Cited by 712 · see citing works
El-Assi, W., Mahmoud, M. S., & Habib, K. N. (2015) · Transportation · doi:10.1007/s11116-015-9669-z · Cited by 571 · see citing works
Faghih-Imani, A., Eluru, N., El-Geneidy, A., et al. (2014) · Journal of Transport Geography · doi:10.1016/j.jtrangeo.2014.01.013 · Cited by 491 · see citing works
Promoting bike-and-ride: The Dutch experience
Martens, K. (2006) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2006.09.010 · Cited by 375 · see citing works
Mining bicycle sharing data for generating insights into sustainable transport systems
O’Brien, O., Cheshire, J. A., & Batty, M. (2013) · Journal of Transport Geography · doi:10.1016/j.jtrangeo.2013.06.007 · Cited by 373 · see citing works
Bachand-Marleau, J., Lee, B. H. Y., & El-Geneidy, A. (2012) · Transportation Research Record Journal of the Transportation Research Board · doi:10.3141/2314-09 · Cited by 344 · see citing works
Insurance, S. (1948) · Medical Entomology and Zoology · Cited by 335 · see citing works
Understanding Bike-Sharing Systems using Data Mining: Exploring Activity Patterns
Vogel, P., Greiser, T., & Mattfeld, D. C. (2011) · Procedia - Social and Behavioral Sciences · doi:10.1016/j.sbspro.2011.08.058 · Cited by 310 · see citing works
Sensing and predicting the pulse of the city through shared bicycling
Froehlich, J. E., Neumann, J., & Oliver, N. (2009) · Cited by 307 · see citing works
Station-Level Forecasting of Bikesharing Ridership
Rixey, R. A. (2013) · Transportation Research Record Journal of the Transportation Research Board · doi:10.3141/2387-06 · Cited by 284 · see citing works
Wang, X., Lindsey, G. H., Schoner, J. E., et al. (2015) · Journal of Urban Planning and Development · doi:10.1061/(asce)up.1943-5444.0000273 · Cited by 278 · see citing works
Zhang, Y., Thomas, T., Brussel, M. J. G., et al. (2016) · Journal of Transport Geography · doi:10.1016/j.jtrangeo.2016.11.014 · Cited by 263 · see citing works
SHARED BICYCLES IN A CITY: A SIGNAL PROCESSING AND DATA ANALYSIS PERSPECTIVE
Borgnat, P., Abry, P., Flandrin, P., Robardet, C., Rouquier, J., & Eric Fleury, B. (2011) · Advances in Complex Systems · doi:10.1142/s0219525911002950 · Cited by 252 · see citing works
Faghih-Imani, A., & Eluru, N. (2016) · Journal of Transport Geography · doi:10.1016/j.jtrangeo.2016.06.008 · Cited by 235 · see citing works
Bike-Share Systems: Accessibility and Availability
Kabra, A., Алексеевна, Б. Е., & Girotra, K. (2019) · Management Science · doi:10.1287/mnsc.2019.3407 · Cited by 218 · see citing works
Introduction to special section on intelligent mobile knowledge discovery and management systems
Xiong, H. Y., Shekhar, S., & Tuzhilin, A. (2013) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/2542182.2542183 · Cited by 206 · see citing works
Analysing bicycle-sharing system user destination choice preferences: Chicago’s Divvy system
Faghih-Imani, A., & Eluru, N. (2015) · Journal of Transport Geography · doi:10.1016/j.jtrangeo.2015.03.005 · Cited by 200 · see citing works
Côme, É., & Oukhellou, L. (2014) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/2560188 · Cited by 182 · see citing works
Measuring the impact of opening the London shared bicycle scheme to casual users
Lathia, N., Ahmed, S., & Capra, L. (2012) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2011.12.004 · Cited by 179 · see citing works
Modeling Bike Sharing System using Built Environment Factors
Tran, T. D., Ovtracht, N., & d’Arcier, B. F. (2015) · Procedia CIRP · doi:10.1016/j.procir.2015.02.156 · Cited by 154 · see citing works
Bike Lanes and Other Determinants of Capital Bikeshare Trips
Buck, D., & Buehler, R. (2012) · Transportation Research Board 91st Annual MeetingTransportation Research Board · Cited by 145 · see citing works
Bordagaray, M. E., dell’Olio, L., Fonzone, A., & Ibeas, Á. (2016) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2016.07.009 · Cited by 93 · see citing works
Strategic and Operational Planning of Bike-Sharing Systems by Data Mining – A Case Study
Vogel, P., & Mattfeld, D. C. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-24264-9_10 · Cited by 78 · see citing works
Krykewycz, G. R., Puchalsky, C. M., Rocks, J., et al. (2010) · Transportation Research Record Journal of the Transportation Research Board · doi:10.3141/2143-15 · Cited by 75 · see citing works
Faghih-Imani, A., & Eluru, N. (2016) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2016.10.024 · Cited by 64 · see citing works
Maximizing bicycle sharing: an empirical analysis of capital bikeshare usage
Daddio, D. (2019) · Carolina Digital Repository (University of North Carolina at Chapel Hill) · doi:10.17615/qv32-b860 · Cited by 52 · see citing works
Hu, H., Voß, S., Stahlbock, R., et al. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33587-7 · Cited by 24 · see citing works
Examining the impact of sample size in the analysis of bicycle-sharing systems
Faghih-Imani, A., & Eluru, N. (2016) · Transportmetrica A Transport Science · doi:10.1080/23249935.2016.1223205 · Cited by 18 · see citing works
Kabra, A., Belavina, E., & Girotra, K. (2016) · Springer series in supply chain management · doi:10.1007/978-3-319-30094-8_8 · Cited by 9 · see citing works
Impact of Built Environment and Temporal Factors on Public Bikesharing
Sun, F., & Chen, P. (2017) · Transportation Research Board 96th Annual MeetingTransportation Research Board · Cited by 5 · see citing works
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Tackling climate change with machine learning
Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A. S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., et al. (2023) · ACM Computing Surveys · doi:10.1145/3485128 · Cited by 336 · see citing works
- Authors
- Hyland, M., Hong, Z., Pinto, H. K. R. D. F., & Chen, Y.
- Affiliations
- Northwestern University (US)
- Corresponding author
- Chen, Ying
- ORCID
- Hyland, Michael
- Venue
- Transportation Research Part A: Policy and Practice
- Publisher
- Elsevier BV
- Published
- 2018-09
- Volume
- 115
- Pages
- 71-89
- ISSN
- 0965-8564 (ISSN-L)
- OpenAlex
- W2777167218
- Cited by
- 83
- References
- 35
- Citations by year
- 2026: 1 · 2025: 11 · 2024: 12 · 2023: 13 · 2022: 9 · 2021: 17 · 2020: 11 · 2019: 4 · 2018: 5
- FWCI
- 7.61
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Transportation Research Part A Policy and Practice (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Northwestern University Transportation Center
- Topics
- Social Sciences › Transportation › Urban Transport and Accessibility
- Physical Sciences › Engineering › Automotive Engineering › Transportation and Mobility Innovations
- Social Sciences › Transportation › Transportation Planning and Optimization
- Keywords
- station clustering, fuzzy c-means clustering, K-means clustering, sociodemographic factors, weather effects, cycling infrastructure
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