Estimation of COVID-19 epidemic cruves using genetic programming algorithm (CROSBI ID 288943)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Anđelić, Nikola ; Baressi Šegota, Sandi ; Lorencin, Ivan ; Mrzljak, Vedran ; Car, Zlatan
engleski
Estimation of COVID-19 epidemic cruves using genetic programming algorithm
This paper investigates the possibility of the implementation of Genetic Programming (GP) algorithm on a publicly available COVID-19 data set, in order to obtain mathematical models which could be used for estimation of confirmed, deceased, and recovered cases and the estimation of epidemiology curve for specific countries, with a high number of cases, such as China, Italy, Spain, and USA and as well as on the global scale. The conducted investigation shows that the best mathematical models produced for estimating confirmed and deceased cases achieved R2 scores of 0.999, while the models developed for estimation of recovered cases achieved the R2 score of 0.998. The equations generated for confirmed, deceased, and recovered cases were combined in order to estimate the epidemiology curve of specific countries and on the global scale. The estimated epidemiology curve for each country obtained from these equations is almost identical to the real data contained within the data set.
COVID-19 ; Disease spread modeling ; Evolutionary computing ; Genetic programming ; Machine Learning
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Podaci o izdanju
27 (1)
2021.
1-40
objavljeno
1460-4582
1741-2811
10.1177/1460458220976728
Povezanost rada
Interdisciplinarne tehničke znanosti, Računarstvo, Temeljne medicinske znanosti