Citation map · Study

SZodixStudyAcademic Library

Dashboard Shelves Open access My library Inbox Notes Write Learn Alerts

More

Ask your library Notifications Quick cite Review

Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated

Towards Station-Level Demand Prediction for Effective Rebalancing in Bike-Sharing Systems

12 references·16 citing·40 second hop

FromToDepth

this work references cited by second hop

References

2015Effects of built environment and weather on bike sharing demand: a station level analysis of commercial bike sharing in Toronto570 cited
2015Traffic prediction in a bike-sharing system361 cited
2014The impact of weather conditions on bikeshare trips in Washington, DC330 cited
2011Understanding Bike-Sharing Systems using Data Mining: Exploring Activity Patterns307 cited
2013Optimal inventory management of a bike-sharing station272 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
2014Model-Based Count Series Clustering for Bike Sharing System Usage Mining: A Case Study with the Vélib’ System of Paris182 cited
2012Measuring the impact of opening the London shared bicycle scheme to casual users176 cited
2012Cityride: A Predictive Bike Sharing Journey Advisor121 cited

Cited by

2022Short-Term Prediction of Bike-Sharing Demand Using Multi-Source Data: A Spatial-Temporal Graph Attentional LSTM Approach52 cited
2020

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

Development of a station-level demand prediction and visualization tool to support bike-sharing systems’ operators

45 cited

2023Forecasting Bike Sharing Demand Using Quantum Bayesian Network42 cited

2020Dynamic bike sharing traffic prediction using spatiotemporal pattern detection36 cited

2021Challenges and Opportunities in Dock-Based Bike-Sharing Rebalancing: A Systematic Review36 cited

2022A hybrid big-data-based and tolerance-based method to estimate environmental benefits of electric bike sharing34 cited

2020Exploiting Interpretable Patterns for Flow Prediction in Dockless Bike Sharing Systems28 cited

2021Enhancing the Accuracy of Peak Hourly Demand in Bike-Sharing Systems using a Graph Convolutional Network with Public Transit Usage Data26 cited

2022Using Machine Learning Methods to Predict Demand for Bike Sharing23 cited

2021Excess demand prediction for bike sharing systems18 cited

2021A Data-Driven Based Dynamic Rebalancing Methodology for Bike Sharing Systems17 cited

2021Monte carlo tree search for dynamic bike repositioning in bike-sharing systems15 cited

2023Discovering spatiotemporal usage patterns of a bike-sharing system by type of pass: a case study from Seoul15 cited

2022Demand-aware mobile bike-sharing service using collaborative computing and information fusion in 5G IoT environment13 cited

2023Understanding the demand predictability of bike share systems: A station-level analysis11 cited

2024Data-driven prioritization strategies for inventory rebalancing in bike-sharing systems11 cited