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Browsing by Author "Sweilam, N.H."

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    Citation - Scopus: 16
    A hybrid fractional COVID-19 model with general population mask use: Numerical treatments
    (Elsevier B.V., 2021) Sweilam, N.H.; Baleanu, Dumitru; AL-Mekhlafi, S.M.; Almutairi, A.; Baleanu, D.; 56389; Matematik
    In this work, a novel mathematical model of Coronavirus (2019-nCov) with general population mask use with modified parameters. The proposed model consists of fourteen fractional-order nonlinear differential equations. Grünwald-Letnikov approximation is used to approximate the new hybrid fractional operator. Compact finite difference method of six order with a new hybrid fractional operator is developed to study the proposed model. Stability analysis of the used methods are given. Comparative studies with generalized fourth order Runge–Kutta method are given. It is found that, the proposed model can be described well the real data of daily confirmed cases in Egypt. © 2021 THE AUTHORS
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    Citation - Scopus: 0
    Optimal control for a variable-order diffusion-wave equation with a reaction term; A numerical study
    (Elsevier B.V., 2024) Sweilam, N.H.; Baleanu, Dumitru; Megahed, F.; Shatta, S.A.; Baleanu, D.; 56389; Matematik
    In this paper, optimal control for a variable-order diffusion-wave equation with a reaction term is numerically studied, where the variable-order operator is defined in the sense of Caputo proportional constant. Necessary optimality conditions for the control problem are derived. Existence and uniqueness for the solutions of fractional optimal control problem are derived. The nonstandard weighted average finite difference method and the nonstandard leap-frog method are developed to study numerically the proposed problem. Moreover, the stability analysis of the methods is proved. Finally, in order to characterise the memory property of the proposed model, three test examples are given. It is found that the nonstandard weighted average finite difference method can be applied to study such variable-order fractional optimal control problems simply and effectively. © 2024 The Author(s)