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Modeling bike availability in a bike-sharing system using machine learning

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References

2010Bikesharing in Europe, the Americas, and Asia1,149 cited
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
2011Understanding Bike-Sharing Systems using Data Mining: Exploring Activity Patterns307 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
2011A Seasonal Autoregressive Model Of Vancouver Bicycle Traffic Using Weather Variables66 cited

Cited by

2019Dynamic linear models to predict bike availability in a bike sharing system38 cited
2018Short-term Prediction of Bike-sharing Usage Considering Public Transport: A LSTM Approach30 cited
2019Multi Features and Multi-time steps LSTM Based Methodology for Bike Sharing Availability Prediction29 cited
2020A Deep Learning Based Multi-Block Hybrid Model for Bike-Sharing Supply-Demand Prediction27 cited
2019Analysis of Spatial and Temporal Characteristics of Citizens’ Mobility Based on E-Bike GPS Trajectory Data in Tengzhou City, China26 cited
2021A framework for estimating bikeshare origin destination flows using a multiple discrete continuous system19 cited

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2020

Optimal Relocation Strategy for Public Bike System with Selective Pick-Up and Delivery

14 cited

2022Quality of Service Measure for Bike Sharing Systems9 cited

2021A Real-Time Bike Trip Planning Policy With Self-Organizing Bike Redistribution7 cited

2021UniCycle: An Android Application of Bike Sharing System in the Digital Campus6 cited

2022Digital Bicycling Planning: A Systematic Literature Review of Data-Driven Approaches6 cited

2021Stochastic bi-objective optimisation formulation for bike-sharing system fleet deployment5 cited

2021A crowdsourced dynamic repositioning strategy for public bike sharing systems5 cited

2024AdaBoost.RDT: AdaBoost Integrated With Residual-Based Decision Tree for Demand Prediction of Bike Sharing Systems Under Extreme Demands4 cited

2021Can user data improve Bike Sharing Systems demand forecasting?4 cited

2022Shared Cycling Demand Prediction during COVID-19 Combined with Urban Computing and Spatiotemporal Residual Network4 cited