Cited by

• 2019A model framework for discovering the spatio-temporal usage patterns of public free-floating bike-sharing system195 cited
• 2020Using data mining techniques for bike sharing demand prediction in metropolitan city164 cited
• 2019A Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems158 cited
• 2020Using graph structural information about flows to enhance short-term demand prediction in bike-sharing systems116 cited
• 2019Consolidated, systemic conceptualization, and definition of the “sharing economy”115 cited
• 2019Citywide Bike Usage Prediction in a Bike-Sharing System106 cited
• 2018Dynamic Bike Reposition96 cited
• 2019Predicting bike sharing demand using recurrent neural networks90 cited
• 2020An Attention-Based Deep Learning Framework for Trip Destination Prediction of Sharing Bike78 cited
• 2019Estimating the parking demand of free-floating bike sharing: A journey-data-based study of Nanjing, China77 cited
• 2020A Hybrid Machine Learning Model for Demand Prediction of Edge-Computing-Based Bike-Sharing System Using Internet of Things73 cited
• 2022Predictive and prescriptive performance of bike-sharing demand forecasts for inventory management65 cited
• 2020Predicting station level demand in a bike‐sharing system using recurrent neural networks63 cited
• 2021Machine Learning Approaches to Bike-Sharing Systems: A Systematic Literature Review62 cited
• 2022Bike-Sharing Demand Prediction at Community Level under COVID-19 Using Deep Learning57 cited
• 2020What is the Human Mobility in a New City: Transfer Mobility Knowledge Across Cities54 cited