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

Samaneh Soradi Zeid and Mostafa Yousefi

International Journal of Sciences, 2016, vol. 5, issue 06, 65-69

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 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.ijsciences.com/pub/article/1044 (text/html)
https://www.ijsciences.com/pub/pdf/V52016061044.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:adm:journl:v:5:y:2016:i:6:p:65-69

Ordering information: This journal article can be ordered from
https://www.ijsciences.com/payment_guide.php

DOI: 10.18483/ijSci.1044

Access Statistics for this article

More articles in International Journal of Sciences from Office ijSciences Alkhaer Publications Manchester M8 8XG England.
Bibliographic data for series maintained by Staff ijSciences ().