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Prediction of bike-sharing station demand using explainable artificial intelligence
16 references·0 citing·38 second hop
Prediction of bike-sharing station demand using explainable artificial intelligence (2024)Prediction of bike-sharing station demand…Predicting the travel mode choice with interpretable machine learning techniques: A comparative study (2022)Predicting the travel mode ch…A review on bike-sharing: The factors affecting bike-sharing demand (2019)A review on bike-sharing: The…A model framework for discovering the spatio-temporal usage patterns of public free-floating bike-sharing system (2019)A model framework for discove…A Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems (2019)A Deep Reinforcement Learning…The station-free sharing bike demand forecasting with a deep learning approach and large-scale datasets (2018)The station-free sharing bike…Bike sharing differences among Millennials, Gen Xers, and Baby Boomers: Lessons learnt from New York City’s bike share (2018)Bike sharing differences amon…A Dynamic Approach to Rebalancing Bike-Sharing Systems (2018)A Dynamic Approach to Rebalan…Exploring the impact of built environment factors on the use of public bikes at bike stations: Case study in Zhongshan, China (2016)Exploring the impact of built…Modeling Bike Sharing System using Built Environment Factors (2015)Modeling Bike Sharing System …Modeling Bike Share Station Activity: Effects of Nearby Businesses and Jobs on Trips to and from Stations (2015)Modeling Bike Share Station A…Effects of built environment and weather on bike sharing demand: a station level analysis of commercial bike sharing in Toronto (2015)Effects of built environment …How land-use and urban form impact bicycle flows: evidence from the bicycle-sharing system (BIXI) in Montreal (2014)How land-use and urban form i…Station-Level Forecasting of Bikesharing Ridership (2013)Station-Level Forecasting of …Better Understanding of Factors Influencing Likelihood of Using Shared Bicycle Systems and Frequency of Use (2012)Better Understanding of Facto…Barriers and facilitators to public bicycle scheme use: A qualitative approach (2012)Barriers and facilitators to …Strategic design of public bicycle sharing systems with service level constraints (2010)Strategic design of public bi…Social Learning Theory. (1978)Using thematic analysis in psychology (2006)Bikesharing in Europe, the Americas, and Asia (2010)Factors influencing bike share membership: An analysis of Melbourne and Brisbane (2014)Intentions to use bike-sharing for holiday cycling: An application of the Theory of Planned Behavior (2014)A comparison in travel patterns and determinants of user demand between docked and dockless bike-sharing systems using multi-sourced data (2020)How the built environment affects physical activity (2002)Obesity relationships with community design, physical activity, and time spent in cars (2004)Bikeshare trip generation in New York City (2016)A modeling framework for the dynamic management of free-floating bike-sharing systems (2018)Bike-sharing: History, Impacts, Models of Provision, and Future (2009)Bike Share: A Synthesis of the Literature (2013)Bike sharing: A review of evidence on impacts and processes of implementation and operation (2015)Environmental benefits of bike sharing: A big data-based analysis (2018)THE MAXIMAL COVERING LOCATION PROBLEM (1974)Discrete location theory (1991)Facility location : applications and theory (2001)Optimizing the location of stations in bike-sharing programs: A GIS approach (2012)Traffic prediction in a bike-sharing system (2015)Internet, Mail, and Mixed-Mode Surveys: The Tailored Design Method (2008)Internet, mail, and mixed-mode surveys: The tailored design method * (2010)Are Bikeshare Users Different from Regular Cyclists? (2013)The impact of weather conditions on bikeshare trips in Washington, DC (2014)Travel and the Built Environment: A Synthesis (2001)Environmental correlates of walking and cycling: Findings from the transportation, urban design, and planning literatures (2003)Built environment effects on the integration of dockless bike-sharing and the metro (2020)Travel demand and the 3Ds: Density, diversity, and design (1997)Travel and the Built Environment (2010)Bike-sharing systems and congestion: Evidence from US cities (2017)Unravel the landscape and pulses of cycling activities from a dockless bike-sharing system (2019)Dockless bike-sharing as a feeder mode of metro commute? The role of the feeder-related built environment: Analytical framework and empirical evidence (2020)Statistical and Econometric Methods for Transportation Data Analysis (2003)Deep learning with long short-term memory networks for financial market predictions (2017)Identifying the nonlinear relationship between free-floating bike sharing usage and built environment (2020)Commuting by Bicycle: An Overview of the Literature (2009)Sustainable Mobility: A Review of Possible Actions and Policies (2020)The link between bike sharing and subway use during the COVID-19 pandemic: The case-study of New York's Citi Bike (2020)Dockless bike-sharing systems: what are the implications? (2020)
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References

  • 2015Effects of built environment and weather on bike sharing demand: a station level analysis of commercial bike sharing in Toronto570 cited
  • 2014How land-use and urban form impact bicycle flows: evidence from the bicycle-sharing system (BIXI) in Montreal486 cited
  • 2019A review on bike-sharing: The factors affecting bike-sharing demand460 cited
  • 2010Strategic design of public bicycle sharing systems with service level constraints435 cited
  • 2012Better Understanding of Factors Influencing Likelihood of Using Shared Bicycle Systems and Frequency of Use342 cited
  • 2012Barriers and facilitators to public bicycle scheme use: A qualitative approach317 cited
  • 2018The station-free sharing bike demand forecasting with a deep learning approach and large-scale datasets291 cited
  • 2013Station-Level Forecasting of Bikesharing Ridership277 cited
  • 2015Modeling Bike Share Station Activity: Effects of Nearby Businesses and Jobs on Trips to and from Stations275 cited
  • 2016Exploring the impact of built environment factors on the use of public bikes at bike stations: Case study in Zhongshan, China258 cited
  • 2019A model framework for discovering the spatio-temporal usage patterns of public free-floating bike-sharing system195 cited
  • 2018Bike sharing differences among Millennials, Gen Xers, and Baby Boomers: Lessons learnt from New York City’s bike share185 cited
  • 2022Predicting the travel mode choice with interpretable machine learning techniques: A comparative study

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170 cited
  • 2019A Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems158 cited
  • 2015Modeling Bike Sharing System using Built Environment Factors152 cited
  • 2018A Dynamic Approach to Rebalancing Bike-Sharing Systems147 cited
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