Numerical modeling of HIV dynamics in CD4+ T-cells using fuzzy differential equations
Abstract
In this study, we use fuzzy differential equations (FDEs) to present a mathematical model for the dynamics of HIV infection in CD4+ T-cells. Uninfected cells, infected cells, and viral particles, all of which are represented as fuzzy dynamical systems, are the three main components of the model. We use ρ-cut techniques to convert the fuzzy system into a corresponding crisp system of differential equations to analyze the spread and control of HIV. Equilibrium points and eigenvalue-based criteria are used in stability analysis. In addition, we derive approximate solutions using the fifth-order Runge-Kutta numerical approach. The suggested method provides a more adaptable and practical framework for understanding the dynamics of HIV infection in an environment of uncertainty.
- Published
- 7 November 2025
- Volume
- 2025 (2025)
- License
- CC BY 3.0
Copyright © 2025 T. Muthukumar, R. Ramesh, L. Chitra, K. Kalaiselvi, L. Senthil Kumar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Cite this article
T. Muthukumar, R. Ramesh, L. Chitra, K. Kalaiselvi, L. S. Kumar, Numerical modeling of HIV dynamics in CD4+ T-cells using fuzzy differential equations, Commun. Math. Biol. Neurosci. 2025 (2025), 131. https://doi.org/10.28919/cmbn/9424
BibTeX
@article{Muthukumar2025,
author = {Muthukumar, T. and Ramesh, R. and Chitra, L. and Kalaiselvi, K. and Kumar, L. Senthil},
title = {Numerical modeling of HIV dynamics in CD4+ T-cells using fuzzy differential equations},
journal = {Commun. Math. Biol. Neurosci.},
volume = {2025},
year = {2025},
pages = {131},
doi = {10.28919/cmbn/9424}
}