Identifying and ranking high-demand areas in a bike-sharing system based on extreme value theory
Bibliographic Data
| ID | 21234441 |
|---|---|
| Authors | Lixuan An (0000-0001-5184-2206, Ghent University, corresponding author), Bernard De Baets (0000-0002-3876-620X, Ghent University), Lisheng Jiang (Chengdu University of Technology), Stijn Luca (0000-0002-6781-7870, Ghent University) |
| Year | 2026 |
| Volume | 148 |
| Pages | 107615 |
| Publication date | 2026-09-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Sustainable Cities and Society (JOURNAL) |
| Journal identifiers | ISSN: 2210-6707 • E-ISSN: 2210-6715 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.scs.2026.107615 |
| OpenAlex | W7165495956 |
| Language | EN |
| References cited | 43 |
Anomaly detection · Computational complexity theory · Interpretability · Key (lock) · Probabilistic logic · Ranking (information retrieval) · Scalability · Human Mobility and Location-Based Analysis · Urban and Freight Transport Logistics · Urban Transport and Accessibility
A review on bike-sharing
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Understanding spatial-temporal travel demand of free-floating bike sharing connecting with metro stations
Revealing the driving factors and mobility patterns of bike-sharing commuting demands for integrated public transport systems
The association between travel demand of docked bike-sharing and the built environment
Revealing the travel community in the integrated system of free-floating bike and metro
Considering user behavior in free-floating bike sharing system design
Analysis of integrated uses of dockless bike sharing and ridesourcing with metros
Integration of dockless bike-sharing and metro
The spatially varying effects of built environment characteristics on the integrated usage of dockless bike-sharing and public transport
Deciphering flow clusters from large-scale free-floating bike sharing journey data
Unsupervised machine learning in urban studies
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Examining spatiotemporal changing patterns of bike-sharing usage during Covid-19 pandemic
Using GIS to visualise and evaluate student travel behaviour
Investigation on the effects of weather and calendar events on bike-sharing according to the trip patterns of bike rentals of stations
Deciphering urban bike-sharing patterns
Modeling activity spaces using big geo-data
| Citation velocity | historical |
|---|---|
| Highly cited | No |