Pengxiang Zhao
Forskare
A machine learning based approach for predicting usage efficiency of shared e-scooters using vehicle availability data
Författare
Redaktör
- E. Parseliunas
- A. Mansourian
- P. Partsinevelos
- J. Suziedelyte-Visockiene
Summary, in English
Avdelning/ar
- Centrum för Mellanösternstudier (CMES)
- MECW: The Middle East in the Contemporary World
- Institutionen för naturgeografi och ekosystemvetenskap
- Centrum för geografiska informationssystem (GIS-centrum)
- BECC: Biodiversity and Ecosystem services in a Changing Climate
Publiceringsår
2022
Språk
Engelska
Publikation/Tidskrift/Serie
AGILE: GIScience Series, 3, 20, 2022
Volym
3
Dokumenttyp
Konferensbidrag
Förlag
Copernicus GmbH
Ämne
- Earth and Related Environmental Sciences
Nyckelord
- Micro-mobility
- E-scootersharing
- Usage efficiency
- Spatiotemporalanalysis
- Machine learning
- Vehicle availability data
- Artificial Intelligence (AI)
- Geospatial Artificial Intelligence (GeoAI)
Conference name
25th AGILE Conference on Geographic Information Science
Conference date
2022-06-14 - 2022-06-17
Conference place
Vilnius, Lithuania
Status
Published