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Numerical solution and parameter estimation for uncertain SIR model with application to COVID-19
Developing algorithms for solving high-dimensional uncertain differential equations has been an exceedingly difficult task. This paper presents an [Formula: see text] -path-based approach that can handle the proposed high-dimensional uncertain SIR model. We apply the [Formula: see text] -path-based...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7495411/ http://dx.doi.org/10.1007/s10700-020-09342-9 |
Sumario: | Developing algorithms for solving high-dimensional uncertain differential equations has been an exceedingly difficult task. This paper presents an [Formula: see text] -path-based approach that can handle the proposed high-dimensional uncertain SIR model. We apply the [Formula: see text] -path-based approach to calculating the uncertainty distributions and related expected values of the solutions. Furthermore, we employ the method of moments to estimate parameters and design a numerical algorithm to solve them. This model is applied to describing the development trend of COVID-19 using infected and recovered data of Hubei province. The results indicate that lockdown policy achieves almost 100% efficiency after February 13, 2020, which is consistent with the existing literatures. The high-dimensional [Formula: see text] -path-based approach opens up new possibilities in solving high-dimensional uncertain differential equations and new applications. |
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