An Intelligent Rebalance System for Tidal Phenomenon of Dockless Bicycle-Sharing

With the advantages of flexible parking locations and convenient cycling, Dockless Bicycle-sharing (DBS) has become increasingly popular worldwide. However, with massive increase DBSs electric fences, DBS systems face several challenges: (1) hardness identifying tidal zones; (2) difficulty accurately evaluating overload fences; (3) issues rebalancing in time. To deal these challenges, we propose a Dynamic Rebalance (DBSDR) system to dynamically provide optimal bicycle guidance for network. The DBSDR contains three modules: zone identification, evaluation framework dynamic guidance. For identification location from each fence flows are provided HDBSCAN clustering method. framework, covering demand density, is proposed assess characteristics fences. Finally, method balance phenomenon guiding users target fence. Extensive experiments conducted on real-world datasets show effectiveness accuracy system.