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Numerical Investigations through ANNs for Solving COVID-19 Model.

Muhammad UmarZulqurnain SabirMuhammad Asif Zahoor RajaShumaila JaveedHijaz AhmadSayed K ElagenAhmed Khames
Published in: International journal of environmental research and public health (2021)
The current investigations of the COVID-19 spreading model are presented through the artificial neuron networks (ANNs) with training of the Levenberg-Marquardt backpropagation (LMB), i.e., ANNs-LMB. The ANNs-LMB scheme is used in different variations of the sample data for training, validation, and testing with 80%, 10%, and 10%, respectively. The approximate numerical solutions of the COVID-19 spreading model have been calculated using the ANNs-LMB and compared viably using the reference dataset based on the Runge-Kutta scheme. The obtained performance of the solution dynamics of the COVID-19 spreading model are presented based on the ANNs-LMB to minimize the values of fitness on mean square error (M.S.E), along with error histograms, regression, and correlation analysis.
Keyphrases
  • coronavirus disease
  • sars cov
  • physical activity
  • body composition
  • respiratory syndrome coronavirus
  • machine learning
  • big data
  • virtual reality