Simanga Phila Gwebu

Mr. Simanga Phila Gwebu


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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10 March 2022 in Axioms
Verified
Journal Article
Open access
PDF file
Joseph MalinziJoseph Malinzi
Joseph Malinzi
SGSimanga Phila Gwebu
Simanga Phila Gwebu
SMSandile Motsa
Sandile Motsa
The Physics Informed Neural Networks framework is applied to the understanding of the dynamics of COVID-19. To provide the governing system of equations used by the framework, the Susceptible–Infected–Recovered–Death mathematical model is used. This study focused on finding the patterns of the dynamics of the disease which involves predicting the infection rate, recovery rate and death rate; thus, predicting the active infections, total recovered, susceptible and deceased at any required time. The study used data that were collected on the dynamics of COVID-19 from the Kingdom of Eswatini between March 2020 and September 2021. The obtained results could be used for making future forecasts on COVID-19 in Eswatini.