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• W3016692394 abstract "Calibration of a SIR (Susceptibles-Infected-Recovered) model with official international data for the COVID-19 pandemics provides a good example of the difficulties inherent the solution of inverse problems. Inverse modeling is set up in a framework of discrete inverse problems, which explicitly considers the role and the relevance of data. Together with a physical vision of the model, the present work addresses numerically the issue of parameters calibration in SIR models, it discusses the uncertainties in the data provided by international authorities, how they influence the reliability of calibrated model parameters and, ultimately, of model predictions." @default.
• W3016692394 created "2020-04-24" @default.
• W3016692394 creator A5049442182 @default.
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• W3016692394 date "2020-04-16" @default.
• W3016692394 modified "2023-09-27" @default.
• W3016692394 title "Inversion of a SIR-based model: a critical analysis about the application to COVID-19 epidemic" @default.
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• W3016692394 hasPublicationYear "2020" @default.
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