Name
Abstract | ||
|---|---|---|
Bicycle sharing systems are becoming increasingly prevalent in urban environments. These systems provide an environmentally friendly transportation alternative in cities. The management of these systems faces many optimization problems. The most important of these problems are the individual maintenance of bicycles, rebalancing and shared facilities, and the use of systems by creating requirements in asymmetrical patterns. A series of data mining tasks based on real data sets is performed to solve the problem of unbalanced bicycle use. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.future.2018.12.017 | Future Generation Computer Systems |
Keywords | Field | DocType |
Public bicycle services,Data analytics,Artificial intelligence,Intelligent transportation | Data science,Data set,Data analysis,Computer science,Environmentally friendly,Effective method,Optimization problem,Distributed computing | Journal |
Volume | ISSN | Citations |
95 | 0167-739X | 1 |
PageRank | References | Authors |
0.42 | 0 | 5 |