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An XGBoost-Based Three-Stage Prediction Approach for True User Demand of Bike-Sharing Systems Based on Spatio-Temporal Analysis
16 references·0 citing·43 second hop
An XGBoost-Based Three-Stage Prediction Approach for True User Demand of Bike-Sharing Systems Based on Spatio-Temporal Analysis (2025)An XGBoost-Based Three-Stage Prediction A…Using graph structural information about flows to enhance short-term demand prediction in bike-sharing systems (2020)Using graph structural inform…An Attention-Based Deep Learning Framework for Trip Destination Prediction of Sharing Bike (2020)An Attention-Based Deep Learn…Data Management Challenges for Deep Learning (2019)Data Management Challenges fo…Understanding the usage of dockless bike sharing in Singapore (2018)Understanding the usage of do…Investigation on the effects of weather and calendar events on bike-sharing according to the trip patterns of bike rentals of stations (2018)Investigation on the effects …A modeling framework for the dynamic management of free-floating bike-sharing systems (2018)A modeling framework for the …Setting Inventory Levels in a Bike Sharing Network (2017)Setting Inventory Levels in a…Incorporating the impact of spatio-temporal interactions on bicycle sharing system demand: A case study of New York CitiBike system (2016)Incorporating the impact of s…Dynamic cluster-based over-demand prediction in bike sharing systems (2016)Dynamic cluster-based over-de…Bike-share rebalancing strategies, patterns, and purpose (2016)Bike-share rebalancing strate…Traffic prediction in a bike-sharing system (2015)Traffic prediction in a bike-…Optimizing the level of service quality of a bike-sharing system (2015)Optimizing the level of servi…Global bike share: What the data tells us about road safety (2015)Global bike share: What the d…Measuring the impact of opening the London shared bicycle scheme to casual users (2012)Measuring the impact of openi…Cityride: A Predictive Bike Sharing Journey Advisor (2012)Cityride: A Predictive Bike S…SHARED BICYCLES IN A CITY: A SIGNAL PROCESSING AND DATA ANALYSIS PERSPECTIVE (2011)SHARED BICYCLES IN A CITY: A …Sensing and predicting the pulse of the city through shared bicycling (2009)Structure of Urban Movements: Polycentric Activity and Entangled Hierarchical Flows (2011)Incentivizing Users for Balancing Bike Sharing Systems (2015)An empirical analysis of bike sharing usage and rebalancing: Evidence from Barcelona and Seville (2017)Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis (2006)Washington DC - USA (2008)Bikesharing in Europe, the Americas, and Asia (2010)Big Data and Cycling (2015)Exploring bikesharing travel time and trip chain by gender and day of the week (2015)Bike sharing use in conjunction to public transport: Exploring spatiotemporal, age and gender dimensions in Oslo, Norway (2020)Bike-sharing: History, Impacts, Models of Provision, and Future (2009)Urban cycles and mobility patterns: Exploring and predicting trends in a bicycle-based public transport system (2010)Planning Bike Lanes based on Sharing-Bikes' Trajectories (2017)Specification and Estimation of Spatial Panel Data Models (2003)Bike sharing differences among Millennials, Gen Xers, and Baby Boomers: Lessons learnt from New York City’s bike share (2018)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)Stochastic Simulation (1987)Infrastructure, programs, and policies to increase bicycling: An international review (2009)A Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems (2019)A spatiotemporal and graph-based analysis of dockless bike sharing patterns to understand urban flows over the last mile (2019)Social Sensing: A New Approach to Understanding Our Socioeconomic Environments (2015)A rule-based model for Seoul Bike sharing demand prediction using weather data (2020)Bikeshare and subway ridership changes during the COVID-19 pandemic in New York City (2021)Strategic design of public bicycle sharing systems with service level constraints (2010)Understanding Bike-Sharing Systems using Data Mining: Exploring Activity Patterns (2011)Optimizing the location of stations in bike-sharing programs: A GIS approach (2012)Mapping the bike sharing research published from 2010 to 2018: A scientometric review (2018)A model framework for discovering the spatio-temporal usage patterns of public free-floating bike-sharing system (2019)How Accessibility Shapes Land Use (1959)Travel and the Built Environment: A Synthesis (2001)Travel and the Built Environment (2010)Understanding intention and behavior toward sustainable usage of bike sharing by extending the theory of planned behavior (2019)A comparison in travel patterns and determinants of user demand between docked and dockless bike-sharing systems using multi-sourced data (2020)Dockless bike-sharing systems: what are the implications? (2020)Deep learning applications and challenges in big data analytics (2015)Qualitative Case Study Methodology: Study Design and Implementation for Novice Researchers (2015)Doing a thematic analysis: A practical, step-by-step guide for learning and teaching scholars. (2017)Data Pipeline Management in Practice: Challenges and Opportunities (2020)Open Data Ecosystems — An empirical investigation into an emerging industry collaboration concept (2021)Rebalancing Bike Sharing Systems (2016)Quantifying greenhouse gas emissions reduction from bike share systems: a model considering real-world trips and transportation mode choice patterns (2019)A review of bicycle-sharing service planning problems (2020)
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References

  • 2018Understanding the usage of dockless bike sharing in Singapore421 cited
  • 2015Traffic prediction in a bike-sharing system361 cited
  • 2018A modeling framework for the dynamic management of free-floating bike-sharing systems269 cited
  • 2011SHARED BICYCLES IN A CITY: A SIGNAL PROCESSING AND DATA ANALYSIS PERSPECTIVE251 cited
  • 2016Incorporating the impact of spatio-temporal interactions on bicycle sharing system demand: A case study of New York CitiBike system235 cited
  • 2015Optimizing the level of service quality of a bike-sharing system218 cited
  • 2016Dynamic cluster-based over-demand prediction in bike sharing systems204 cited
  • 2012Measuring the impact of opening the London shared bicycle scheme to casual users176 cited
  • 2018Investigation on the effects of weather and calendar events on bike-sharing according to the trip patterns of bike rentals of stations174 cited
  • 2019Data Management Challenges for Deep Learning130 cited
  • 2012Cityride: A Predictive Bike Sharing Journey Advisor121 cited
  • 2020Using graph structural information about flows to enhance short-term demand prediction in bike-sharing systems116 cited
  • 2017Setting Inventory Levels in a Bike Sharing Network108 cited
  • 2016Bike-share rebalancing strategies, patterns, and purpose105 cited

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  • 2020An Attention-Based Deep Learning Framework for Trip Destination Prediction of Sharing Bike78 cited
  • 2015Global bike share: What the data tells us about road safety78 cited
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