Multitask learning and nonlinear optimal control of the COVID-19 outbreak: A geometric programming approach()

We propose a multitask learning approach to learn the parameters of a compartmental discrete-time epidemic model from various data sources and use it to design optimal control strategies of human-mobility restrictions that both curb the epidemic and minimize the economic costs associated with implem...

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Detalles Bibliográficos
Autores principales: Hayhoe, Mikhail, Barreras, Francisco, Preciado, Victor M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Full Length Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8133409/
https://www.ncbi.nlm.nih.gov/pubmed/34040494
http://dx.doi.org/10.1016/j.arcontrol.2021.04.014

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8133409/
https://www.ncbi.nlm.nih.gov/pubmed/34040494
http://dx.doi.org/10.1016/j.arcontrol.2021.04.014

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