| Autor: |
Sa'adah, Aminatus, Saragih, Roberd, Handayani, Dewi |
| Předmět: |
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| Zdroj: |
International Journal of Electrical & Computer Engineering (2088-8708); Oct2024, Vol. 14 Issue 5, p5117-5130, 14p |
| Abstrakt: |
Millions of people died worldwide as a result of the coronavirus disease 2019 (COVID-19) pandemic that started in early 2020. Examining the COVID-19 susceptible-exposed-infected-recovery (SEIR) mathematical model is one approach to developing the best control scenario for this disease. The study utilized two control variables, vaccination, and therapy, to construct a control function that relied on the quadratic Lyapunov function. The control objective was to lower the number of COVID-19 infections while maintaining system stability. A genetic algorithm (GA) is used as a novel method to estimate controller parameter value to replace the previously used parameter tuning procedure. Then, a numerical simulation was carried out implementing three control scenarios, namely vaccination control only, treatment control only, and vaccination and treatment control simultaneously. Based on the results, scenario 3 (vaccination and treatment simultaneously) showed the most significant decrease: the average decrease in the exposed human population was 98.29%, and the infected human population was 98.18%. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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