Beler, Ayşe

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Profile URL
https://hdl.handle.net/20.500.14365/6735
Name Variants
Beler, A.
Beler, Ayse
Job Title
Email Address
ayse.beler@ieu.edu.tr
Main Affiliation
02.02. Mathematics
Status
Current Staff
Website
ORCID ID
0000-0003-4414-3727
Scopus Author ID
58130681500
Turkish CoHE Profile ID
AF901D756BBCF3C4
Google Scholar ID
LZRnR2AAAAAJ
WoS Researcher ID
IAI-9780-2023
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Ayse_Beler.png (117.4 KB)

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  • Thumbnail Image
    Article
    Citation - Scopus: 1
    Gegenbauer Wavelet Solutions of the Sir and Sitr Systems of the Covid-19 Disease
    (World Scientific Publ Co Pte Ltd, 2024) Simsek, Gokce ozaltun; Beler, Ayse; Gumgum, Sevin
    This study aimed to investigate the influence of various parameters on the solutions of the susceptible-infected-recovered (SIR) and susceptible-treated-infectious-recovering (SITR) models to describe the spread of COVID-19. To achieve this, we employ the Gegenbauer wavelet technique to convert the system of nonlinear differential equations into a system of nonlinear algebraic equations. This approach has the advantage of not requiring the linearization of the nonlinear expressions, which significantly reduces truncation errors commonly associated with other methods. We conduct a thorough comparison of the absolute and residual errors generated by this technique against those produced by other numerical methods, finding that our results demonstrate a high level of accuracy. Additionally, the Gegenbauer wavelet technique is not only efficient but also straightforward to implement, contributing to a lower CPU time requirement. Overall, this study highlights the effectiveness of the Gegenbauer wavelet technique in accurately modeling the dynamics of COVID-19 transmission while offering practical computational advantages.
  • Thumbnail Image
    Article
    Citation - WoS: 6
    Citation - Scopus: 8
    Numerical Solutions of the Hiv Infection Model of Cd4(+) Cells by Laguerre Wavelets
    (Elsevier, 2023) Beler, Ayse; Özaltun, Gökçe; Gümgüm, Sevin; Özaltun Şimşek, Gökçe
    In this study, we analyze the numerical solutions of the Human Immunodeficiency Virus (HIV) infection on helper T cells by using the Laguerre wavelet method. Our goal is to find accurate approximate results of the models that measure the number of helper infected and uninfected T cells as well as the number of free virus particles at a given time. We present two different models which are governed by three first order nonlinear differential equations with different parameters. We include an error analysis in order to compare the results with other methods available in the literature, and observe that the Laguerre wavelet method gives highly accurate results, is very easy to implement, hence efficient, in the solution of the type of problems indicated.(c) 2023 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.