Intelligent computing with Levenberg-Marquardt artificial neural networks for nonlinear system of COVID-19 epidemic model for future generation disease control

Tahir Nawaz Cheema; Muhammad Asif Zahoor Raja; Iftikhar Ahmad; Shafaq Naz; Hira Ilyas; Muhammad Shoaib

doi:10.1140/epjp/s13360-020-00910-x

Intelligent computing with Levenberg-Marquardt artificial neural networks for nonlinear system of COVID-19 epidemic model for future generation disease control

Eur Phys J Plus. 2020;135(11):932. doi: 10.1140/epjp/s13360-020-00910-x. Epub 2020 Nov 23.

Authors

Tahir Nawaz Cheema¹, Muhammad Asif Zahoor Raja^{2

3}, Iftikhar Ahmad¹, Shafaq Naz¹, Hira Ilyas¹, Muhammad Shoaib⁴

Affiliations

¹ Department of Mathematics, University of Gujrat, Gujrat, 50700 Pakistan.
² Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Sect. 3, Douliou, Yunlin, 64002 Taiwan R.O.C.
³ Department of Electrical and Computer Engineering, COMSATS University Islamabad, Attock Campus, Attock, 43600 Pakistan.
⁴ Department of Mathematics, COMSATS University Islamabad, Attock Campus, Attock, 43600 Pakistan.

Abstract

The aim of this work is to design an intelligent computing paradigm through Levenberg-Marquardt artificial neural networks (LMANNs) for solving the mathematical model of Corona virus disease 19 (COVID-19) propagation via human to human interaction. The model is represented with systems of nonlinear ordinary differential equations represented with susceptible, exposed, symptomatic and infectious, super spreaders, infection but asymptomatic, hospitalized, recovery and fatality classes, and reference dataset of the COVID-19 model is generated by exploiting the strength of explicit Runge-Kutta numerical method for metropolitans of China and Pakistan including Wuhan, Karachi, Lahore, Rawalpindi and Faisalabad. The created dataset is arbitrary used for training, validation and testing processes for each cyclic update in Levenberg-Marquardt backpropagation for numerical treatment of the dynamics of COVID-19 model. The effectiveness and reliable performance of the design LMANNs are endorsed on the basis of assessments of achieved accuracy in terms of mean squared error based merit functions, error histograms and regression studies.