Enhancing urban functional regions classification by integrating multi-source data with a heterogeneous graph neural network

Category

Published in:

Abstracts of the ICA
Vol. 7.2024 (03.09.2024), art. no. 191, p. 1-2

Volume:

7.2024

Publication date:

03.09.2024

URN:

urn:nbn:de:0307-20251031-003-8

DOI:

10.5194/ica-abs-7-191-2024

Language:

English

Type of Resource:

Text

Extent:

1 Online-Ressource (Seite 1-2, 812,12 kB) : 1 Illustration, 1 Textdatei (PDF)

Keywords:

urban functional region classification; metro passenger flow data; heterogeneous graph neural network; Klassifizierung funktionaler urbaner Regionen; U‑Bahn‑Fahrgaststromdaten; heterogenes Graph-Neuronales Netzwerk

DDC subject of DNB:

520 Astronomy & allied sciences

URL:

https://doi.org/10.5194/ica-abs-7-191-2024

URL:

https://ica-abs.copernicus.org/articles/7/191/2024/

Link to Raw Object:

https://ica-abs.copernicus.org/articles/7/191/2024/ica-abs-7-191-2024.pdf

Hosting institution:

Wuhan University (WHU) [CN]

Hosting institution:

Internationale Forschungseinrichtungen

Statement of responsibility:

Pengxin Zhang, Min Yang

Bibliographic notes:

Published in: Abstracts of the ICA, Volume 7, 2024 - European Cartographic Conference – EuroCarto 2024; 9–11 September 2024, TU Wien, Vienna, Austria; Editors: Georg Gartner, Florian Ledermann, and Andrea Binn | https://ica-abs.copernicus.org/articles/7/index.html