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