Department of Mathematics, Ghazi University, DG Khan, 32200, Pakistan.
Department of Mathematics, Khawaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, Pakistan.
BMC Infect Dis. 2024 Sep 27;24(1):1051. doi: 10.1186/s12879-024-09329-6.
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.
本研究考察了用于 COVID-19 分数阶模型的混合 NAR-RBFs 网络。COVID-19 的混合 NAR-RBFs 网络,这种病毒在人们努力阻止 COVID-19 大流行的过程中,在许多地区更加猖獗。弄清楚如何制定策略来阻止 COVID-19 在不同年龄段的传播是至关重要的。我们使用混合 NAR-RBFs 网络中的疫情情景作为案例研究,以复制修改后的 COVID-19 的传播。在这项研究工作中,应用不动点理论的一些结果验证了 COVID-19 的存在和稳定性,并证明了唯一解。提出的方法用于研究 COVID-19 对不同年龄段混合 NAR-RBFs 网络的影响,相对先进。还通过利用 Atanga Toufik 技术和分形分数获得了所提出模型的解,这些技术是针对此类传染病问题的先进技术,用于连续监测 COVID-19 在不同年龄段的传播。进行了比较以检查技术的效率,并找到可靠的解决方案,以了解 COVID-19 混合 NAR-RBFs 网络的非线性动力学行为。最后,评估参数以了解疾病的影响,并使用 Matlab 进行实际数值模拟,以观察 COVID-19 混合 NAR-RBFs 网络中这种传染病的实际行为。