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Title Artificial Neural Network Based Computational Framework To Solve SI System Of Covid-19 Non Linear Equation

Author(s) Mudassar Hameed

Abstract The aim of the present study is to design the artificial neural network framework to solve the Susceptible and infected (SI) model of the COVID-19 non-linear equation. Mathematical model for epidemic diseases are non-linear. The approximation of non-linear system of ODE is a challenging task. To model epidemic diseases, many analytical and numerical models are proposed in literature. In recent past, unsupervised artificial neural network gain much attention to solving ODE in different application. In the proposed method, the ReLU artificial neural network has been used for its effectiveness in training and modeling complex relationships of our proposed scheme. The fitness function of the unsupervised error function is used to determine how well the predictions provided by the ANN align with the actual data or the desired outcomes. With the help of an analytical model and numerical solver (ODE-45) result, the MAE is utilized to evaluate the accuracy and reliability of our suggested scheme.

Type Thesis/Dissertation MS

Faculty Engineering and Computer Science

Department Computer Science

Language English

Publication Date 2023-12-18

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