Act2Loc: a synthetic trajectory generation method by combining machine learning and mechanistic models-Reference-Cited by-同舟云学术

Act2Loc: a synthetic trajectory generation method by combining machine learning and mechanistic models

Published:2023-12-12 Issue: Volume: Page:1-25
ISSN:1365-8816
Container-title:International Journal of Geographical Information Science
language:en
Short-container-title:International Journal of Geographical Information Science

Author:

Liu Kang¹^ORCID,Jin Xin¹²^ORCID,Cheng Shifen³^ORCID,Gao Song⁴^ORCID,Yin Ling¹^ORCID,Lu Feng²³

Affiliation:

1. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

2. University of Chinese Academy of Sciences, Beijing, China

3. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

4. Department of Geography, University of Wisconsin-Madison, Madison, WI, USA

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Library and Information Sciences,Geography, Planning and Development,Information Systems

Link

https://www.tandfonline.com/doi/pdf/10.1080/13658816.2023.2292570

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