Discovering optimal strategies for mitigating COVID-19 spread using machine learning: experience from Asia

Discovering optimal strategies for mitigating COVID-19 spread using machine learning: experience from Asia

To inform data-driven decisions in fighting the global pandemic caused by COVID-19, this research develops a spatiotemporal analysis framework under the combination of an ensemble model (random forest regression) and a multi-objective optimization algorithm (NSGA-II). It has been verified for four A...

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Bibliographic Details
Main Authors: Pan, Yue, Zhang, Limao, Yan, Zhenzhen, Lwin, May Oo, Skibniewski, Miroslaw J.
Other Authors: School of Civil and Environmental Engineering
Format: Journal Article
Language:English
Published: 2022
Subjects:
Engineering::Civil engineering
COVID-19
Random Forest Regression
Online Access:https://hdl.handle.net/10356/159901

Internet

https://hdl.handle.net/10356/159901

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