Parameters Estimation of Generalized Richards Model for COVID-19 Cases in Indonesia Using Genetic Algorithm

Maya Rayungsari, Muhammad Aufin, Nurul Imamah

Abstract


In this research, genetic algorithm was implemented to estimate parameters in generalized Richards model by adjusting COVID-19 case data in Indonesia. Data collected were the daily new cases and cumulative number of COVID-19 case in Indonesia from early March to early June 2020, that was reported by databoks.katadata.co.id. The best pair of parameters was selected based on the lowest cost function value, determined from the distance between data with estimated model and real data. Next, model with estimated parameters is used to predict new cases and cumulative cases for upcoming days.
Numerical simulations were carried out so that the peaks and ends of the COVID-19 pandemic can be seen easily.


Keywords


Parameters Estimation; Generalized Richards Model; COVID-19; Genetic Algorithm

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References


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DOI: https://doi.org/10.34312/jjbm.v1i1.6910

Copyright (c) 2020 Maya Rayungsari, Muhammad Aufin, Nurul Imamah

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.


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