Analysis of Hybrid NAR-RBFs Networks for complex non-linear Covid-19 model with fractional operators

The Hybrid NAR-RBFs Networks for COVID-19 fractional order model is examined in this scientific study. Hybrid NAR-RBFs Networks for COVID-19, that is more infectious which is appearing in numerous areas as people strive to stop the COVID-19 pandemic. It is crucial to figure out how to create strategies that would stop the spread of COVID-19 with a different age groups. We used the epidemic scenario in the Hybrid NAR-RBFs Networks as a case study in order to replicate the propagation of the modified COVID-19. In this research work, existence and stability are verified for COVID-19 as well as proved unique solutions by applying some results of fixed point theory. The developed approach to investigate the impact of Hybrid NAR-RBFs Networks due to COVID-19 at different age groups is relatively advanced. Also obtain solutions for a proposed model by utilizing Atanga Toufik technique and fractal fractional which are the advanced techniques for such type of infectious problems for continuous monitoring of spread of COVID-19 in different age groups. Comparisons has been made to check the efficiency of techniques as well as for finding the reliable solutions to understand the dynamical behavior of Hybrid NAR-RBFs Networks for non-linear COVID-19. Finally, the parameters are evaluated to see the impact of illness and present numerical simulations using Matlab to see actual behavior of this infectious disease for Hybrid NAR-RBFs Networks of COVID-19 for different age groups.

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Publication Details

Journal
BMC Infectious Diseases
Published
2024-09-27
DOI
https://doi.org/10.1186/s12879-024-09329-6
Citations
7
Primary Topic
Fractional Differential Equations Solutions
Type
article
Field-Weighted Citation Impact
2.77

Funders

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article

Analysis of Hybrid NAR-RBFs Networks for complex non-linear Covid-19 model with fractional operators

Aqeel Ahmad, Sameh Askar, Muhammad Sultan, Muhammad Farman et al.
7 citations
BMC Infectious Diseases
Fractional Differential Equations Solutions
2.77
article

Analysis of Hybrid NAR-RBFs Networks for complex non-linear Covid-19 model with fractional operators

Aqeel Ahmad, Sameh Askar, Muhammad Sultan, Muhammad Farman, Hijaz Ahmad
article en
7 citations

Abstract

The Hybrid NAR-RBFs Networks for COVID-19 fractional order model is examined in this scientific study. Hybrid NAR-RBFs Networks for COVID-19, that is more infectious which is appearing in numerous areas as people strive to stop the COVID-19 pandemic. It is crucial to figure out how to create strategies that would stop the spread of COVID-19 with a different age groups. We used the epidemic scenario in the Hybrid NAR-RBFs Networks as a case study in order to replicate the propagation of the modified COVID-19. In this research work, existence and stability are verified for COVID-19 as well as proved unique solutions by applying some results of fixed point theory. The developed approach to investigate the impact of Hybrid NAR-RBFs Networks due to COVID-19 at different age groups is relatively advanced. Also obtain solutions for a proposed model by utilizing Atanga Toufik technique and fractal fractional which are the advanced techniques for such type of infectious problems for continuous monitoring of spread of COVID-19 in different age groups. Comparisons has been made to check the efficiency of techniques as well as for finding the reliable solutions to understand the dynamical behavior of Hybrid NAR-RBFs Networks for non-linear COVID-19. Finally, the parameters are evaluated to see the impact of illness and present numerical simulations using Matlab to see actual behavior of this infectious disease for Hybrid NAR-RBFs Networks of COVID-19 for different age groups.

BMC Infectious DiseasesVol. 24(1)
SAIT Polytechnic (CA), Azerbaijan Technical University (AZ), King Saud University (SA), Western Caspian University (AZ), Khwaja Fareed University of Engineering and Information Technology (PK), Ghazi University (PK), Korea University (JP), Lebanese American University (LB), Near East University (CY)
King Saud University
Good health and well-being
Openalex Percentile: Top 10%
Fractional Differential Equations Solutions
2.77
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