Hybrid Learning Model of Global–Local Graph Attention Network and XGBoost for Inferring Origin–Destination Flows
Origin–destination (OD) flows are essential for urban studies, yet their acquisition is often hampered by high costs and privacy constraints. Prevailing inference methodologies inadequately address latent spatial dependencies between non-contiguous and distant areas, which are useful for understandi...
Saved in:
| Main Authors: | Zhenyu Shan, Fei Yang, Xingzi Shi, Yaping Cui |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
|
| Series: | ISPRS International Journal of Geo-Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2220-9964/14/5/182 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Taxi origin and destination demand prediction based on deep learning: a review
by: Dan Peng, et al.
Published: (2023-09-01) -
Competencias Investigativas de los Docentes en Ciencias Sociales Tendencias en las Universidades Latinoamericanas.
by: Naun, et al.
Published: (2025-05-01) -
Clarifying Origin-Destination Flows Using Force-Directed Edge Bundling Layout
by: Liangkui Luo, et al.
Published: (2020-01-01) -
Od Redakcji
by: Jacek Leociak, et al.
Published: (2009-11-01) -
Od Redakcji
by: Redakcja
Published: (2023-03-01)