A Neural Network Approach for Solving Fractional-Order Model of HIV Infection of CD4+T-Cells

A Neural Network Approach for Solving Fractional-Order Model of HIV Infection of CD4+T-Cells

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Author(s)

Author(s): Samaneh Soradi Zeid, Mostafa Yousefi

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DOI: 10.18483/ijSci.1044 306 744 65-69 Volume 5 - Jun 2016

Abstract

In this paper the perceptron neural networks are applied to approximate the solution of Fractional-order model of HIV infection of CD4+T-cells that includes a system of fractional differential equations (FDEs). We converted this model to a system of Volterra integral equations. Then, by using perceptron neural networks ability in approximating a nonlinear function, we propose approximating functions to approach parameters of this system of Volterra integral equations. By obtaining the approximated solution of this system, the unknown parameters of the original fractional HIV model are adjusted. Numerical results illustrate this approach is simple and accurate when applied to systems of FDEs.

Keywords

Fractional HIV infection model, Volterra integral equation, Perceptron neural networks, Fractional differential equation

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International Journal of Sciences is Open Access Journal.
This article is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) License.
Author(s) retain the copyrights of this article, though, publication rights are with Alkhaer Publications.

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