Work

A machine learning solutions approach of a time-delayed stochastic $ \tilde{S}\tilde{E}\tilde{I}\tilde{R}\tilde{V} $ model

Year: 2025

Type: article

Abstract: In this work, we analyze the dynamics of a stochastic $ \tilde{S}\tilde{E}\tilde{I}\tilde{R}\tilde{V} $ model with a time delay. We mainly investigate the time delay's influence on these classes' asymptotic behavior. Furthermore, we examine the existence and stability of disease-free and endemic equilibrium points. To better understand the parameter's effects on the spread of an epidemic, we integrate artificial neural networks with the Bayesian regularization method. Additionally, leveraging physics-informed artificial intelligence (AI) and specialized machine training, we develop an advanced framework for solving systems of partial differential equations (PDEs). This approach enhances the accuracy of predictions and facilitates the optimal control and effective implementation of real-world epidemic management strategies.

Source: Networks and Heterogeneous Media

DOI: 10.3934/nhm.2025030

Authors: Mostafa Zahri, Inayat khan, Rahat Zarin, Amir khan, Rukhsar Ikram

Institutions: University of Sharjah, University of Swat, King Mongkut's University of Technology Thonburi

Language: English

Topic: Mathematical and Theoretical Epidemiology and Ecology Models

Subfield: Public Health, Environmental and Occupational Health

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: diamond

OpenAlex ID: W4411289316