Crossmark

Prediction of human activity intensity using the interactions in physical and social spaces through graph convolutional networks

Crossref DOI link: https://doi.org/10.1080/13658816.2021.1912347

Published Online: 2021-04-20

Published Print: 2021-12-02

Update policy: https://doi.org/10.1080/tandf_crossmark_01

Authors

Li, Mingxiao https://orcid.org/0000-0003-0779-4432
Gao, Song https://orcid.org/0000-0003-4359-6302
Lu, Feng

Liu, Kang

Zhang, Hengcai https://orcid.org/0000-0002-5004-9609
Tu, Wei https://orcid.org/0000-0002-0255-4037
Funding

Funding for this research was provided by:

National Key Research and Development Program (2016YFB0502104)

National Science Foundation (1940091)

National Natural Science Foundation of China (41771436)

National Natural Science Foundation of China (41901391)

National Natural Science Foundation of China (42071360)

Shenzhen Basic Research Program (JCYJ20190807163001783)

Guangdong Province Basic and Applied Basic Research Fund Project (2020A1515111166)

Wisconsin Alumni Research Foundation
More Information

Peer Review Statement: The publishing and review policy for this title is described in its Aims & Scope.

Aim & Scope: http://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=tgis20

Publication History

Received: 2020-02-10

Accepted: 2021-03-23

Published: 2021-04-20