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A stacking model for variation prediction of public bicycle traffic flow
11 references·4 citing·37 second hop
A stacking model for variation prediction of public bicycle traffic flow (2018)A stacking model for variation prediction…Bicycle-Sharing System Analysis and Trip Prediction (2016)Bicycle-Sharing System Analys…Traffic prediction in a bike-sharing system (2015)Traffic prediction in a bike-…Model-Based Count Series Clustering for Bike Sharing System Usage Mining: A Case Study with the Vélib’ System of Paris (2014)Model-Based Count Series Clus…Cityride: A Predictive Bike Sharing Journey Advisor (2012)Cityride: A Predictive Bike S…Understanding Bike-Sharing Systems using Data Mining: Exploring Activity Patterns (2011)Understanding Bike-Sharing Sy…Strategic and Operational Planning of Bike-Sharing Systems by Data Mining – A Case Study (2011)Strategic and Operational Pla…SHARED BICYCLES IN A CITY: A SIGNAL PROCESSING AND DATA ANALYSIS PERSPECTIVE (2011)SHARED BICYCLES IN A CITY: A …Urban cycles and mobility patterns: Exploring and predicting trends in a bicycle-based public transport system (2010)Urban cycles and mobility pat…The role of smart bike-sharing systems in urban mobility (2009)The role of smart bike-sharin…Sensing and predicting the pulse of the city through shared bicycling (2009)Sensing and predicting the pu…Bike-sharing: History, Impacts, Models of Provision, and Future (2009)Bike-sharing: History, Impact…Hybrid machine learning-based approaches for modeling bikeability (2025)Hybrid machine learning-based…Enhancing Sustainable Transportation: AI-Driven Bike Demand Forecasting in Smart Cities (2023)Enhancing Sustainable Transpo…Nonlinear Model-Based Subway Station-Level Peak-Hour Ridership Estimation Approach in the Context of Peak Deviation (2022)Nonlinear Model-Based Subway …Effects of Free-Floating Shared Bicycles on Urban Public Transportation (2019)Effects of Free-Floating Shar…Making Cycling Irresistible: Lessons from The Netherlands, Denmark and Germany (2008)Discovering regions of different functions in a city using human mobility and POIs (2012)Big Data and Cycling (2015)Understanding Spatiotemporal Patterns of Biking Behavior by Analyzing Massive Bike Sharing Data in Chicago (2015)Understanding the impacts of a public transit disruption on bicycle sharing mobility patterns: A case of Tube strike in London (2017)Bikesharing in Europe, the Americas, and Asia (2010)Modelling the potential effect of shared bicycles on public transport travel times in Greater Helsinki: An open data approach (2013)Exploring the impact of built environment factors on the use of public bikes at bike stations: Case study in Zhongshan, China (2016)A modeling framework for the dynamic management of free-floating bike-sharing systems (2018)Time Series Analysis: Forecasting and Control. (1978)Understanding individual human mobility patterns (2008)Limits of Predictability in Human Mobility (2010)Mining bicycle sharing data for generating insights into sustainable transport systems (2013)A review on bike-sharing: The factors affecting bike-sharing demand (2019)Estimating Origin-Destination Flows Using Mobile Phone Location Data (2011)Dynamic Bike Reposition (2018)Towards Station-Level Demand Prediction for Effective Rebalancing in Bike-Sharing Systems (2018)Citywide Bike Usage Prediction in a Bike-Sharing System (2019)Structure of Urban Movements: Polycentric Activity and Entangled Hierarchical Flows (2011)Incentivizing Users for Balancing Bike Sharing Systems (2015)Incorporating the impact of spatio-temporal interactions on bicycle sharing system demand: A case study of New York CitiBike system (2016)An empirical analysis of bike sharing usage and rebalancing: Evidence from Barcelona and Seville (2017)Power-law distributions in empirical data (2018)Hierarchical prediction based on two-level Gaussian mixture model clustering for bike-sharing system (2019)An Attention-Based Deep Learning Framework for Trip Destination Prediction of Sharing Bike (2020)Predicting station level demand in a bike‐sharing system using recurrent neural networks (2020)Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis (2006)The scaling laws of human travel (2006)Large-Scale Vehicle Sharing Systems: Analysis of Vélib' (2012)Bicycling renaissance in North America? An update and re-appraisal of cycling trends and policies (2011)Bikeshare: A Review of Recent Literature (2015)Effects of built environment and weather on bike sharing demand: a station level analysis of commercial bike sharing in Toronto (2015)Dynamic cluster-based over-demand prediction in bike sharing systems (2016)Rebalancing Bike Sharing Systems (2016)Planning Bike Lanes based on Sharing-Bikes' Trajectories (2017)A time-space network flow approach to dynamic repositioning in bicycle sharing systems (2016)Bike Sharing and the Economy, the Environment, and Health-Related Externalities (2018)
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References

  • 2009Bike-sharing: History, Impacts, Models of Provision, and Future1,070 cited
  • 2010Urban cycles and mobility patterns: Exploring and predicting trends in a bicycle-based public transport system446 cited
  • 2015Traffic prediction in a bike-sharing system361 cited
  • 2011Understanding Bike-Sharing Systems using Data Mining: Exploring Activity Patterns307 cited
  • 2009Sensing and predicting the pulse of the city through shared bicycling307 cited
  • 2011SHARED BICYCLES IN A CITY: A SIGNAL PROCESSING AND DATA ANALYSIS PERSPECTIVE251 cited
  • 2009The role of smart bike-sharing systems in urban mobility196 cited
  • 2014Model-Based Count Series Clustering for Bike Sharing System Usage Mining: A Case Study with the Vélib’ System of Paris182 cited
  • 2012Cityride: A Predictive Bike Sharing Journey Advisor121 cited
  • 2016Bicycle-Sharing System Analysis and Trip Prediction84 cited
  • 2011Strategic and Operational Planning of Bike-Sharing Systems by Data Mining – A Case Study79 cited

Cited by

  • 2019Effects of Free-Floating Shared Bicycles on Urban Public Transportation20 cited
  • 2023Enhancing Sustainable Transportation: AI-Driven Bike Demand Forecasting in Smart Cities19 cited
  • 2022Nonlinear Model-Based Subway Station-Level Peak-Hour Ridership Estimation Approach in the Context of Peak Deviation

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9 cited
  • 2025Hybrid machine learning-based approaches for modeling bikeability4 cited