General Letters in Mathematics

Volume 9 - Issue 2 (1) | PP: 53 - 66 Language : English

Optimal models for estimating future infected cases of COVID-19 in Oman

Ahmed Al-Siyabi ,
Mehiddin Al-Baali ,
Anton Purnama
Received Date Revised Date Accepted Date Publication Date
2/11/2020 1/12/2020 21/12/2020 31/1/2021
The recent coronavirus disease 2019 (COVID-19) outbreak is of high importance in research topics due to its fast spreading and high rate of infections across the world. In this paper, we test certain optimal models of forecasting daily new cases of COVID-19 in Oman. It is based on solving a certain nonlinear least-squares optimization problem that determines some unknown parameters in fitting some mathematical models. We also consider extension to these models to predict the future number of infection cases in Oman. The modification technique introduces a simple ratio rate of changes in the daily infected cases. This average ratio is computed by employing the rule of Al-Baali [Numerical experience with a class of self-scaling quasi-Newton algorithms, JOTA, 96 (1998), pp. 533–553], in a sense to be defined, for measuring the infection changes.

How To Cite This Article
Al-Siyabi , A.Al-Baali , M. & Purnama , A. (2021). Optimal models for estimating future infected cases of COVID-19 in Oman . General Letters in Mathematics, 9 (2), 53-66, 10.31559/glm2020.9.2.1

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