MONIC CHEBYSHEV’S FIRST DERIVATIVE PSEUDO-GALERKIN METHOD FOR SOLVING LINEAR AND NONLINEAR IBVPS: REAL-LIFE AND PHYSICAL APPLICATIONS

The computation of the solutions of differential equations (DEs) and integral equations (IEs) has noteworthy aspects due to the fact that these equations’ numerical or analytical solutions can yield applicable benefits in various realms of categories of engineering, physics, biology, and signal processing finance, among others. The pseudo-Galerkin method, as a numerical technique for approximating solutions to various types of differential and integral equations, merges the elements concerning the Galerkin method as well as the collocation methods, turning it into a hybrid mode of approach, providing versatility, efficiency, accuracy along with reduced complexity. Accordingly, this paper uses the pseudo-Galerkin method to solve linear and nonlinear differential equations depending on the monic of Chebyshev’s first derivatives as new basis functions through which new operational matrices for derivatives for the introduced basis function have been formed. In addition, a new linearization relation has been proved. Consequently, this relation and other relations have been used via the pseudo-Galerkin method to transform the given initial boundary value problems (IBVPs) into an algebraic system of equations. The error analysis study verifies the convergence of the proposed method. Finally, elements of accuracy, efficiency, and correctness are investigated by solving several numerical applications and real-life problems, including an environmental pollution model.

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Publication Details

Journal
Fractals
Published
2025-05-28
DOI
https://doi.org/10.1142/s0218348x25402169
Citations
1
Primary Topic
Electromagnetic Simulation and Numerical Methods
Type
article
Field-Weighted Citation Impact
0.73
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article

MONIC CHEBYSHEV’S FIRST DERIVATIVE PSEUDO-GALERKIN METHOD FOR SOLVING LINEAR AND NONLINEAR IBVPS: REAL-LIFE AND PHYSICAL APPLICATIONS

M. El-Kady, Weam G. Alharbi, M. Abdelhakem, Yeliz Karaca et al.
1 citations
Fractals
Electromagnetic Simulation and Numerical Methods
0.73
article

MONIC CHEBYSHEV’S FIRST DERIVATIVE PSEUDO-GALERKIN METHOD FOR SOLVING LINEAR AND NONLINEAR IBVPS: REAL-LIFE AND PHYSICAL APPLICATIONS

M. El-Kady, Weam G. Alharbi, M. Abdelhakem, Yeliz Karaca, Gaitha M. Alzabeedy, HAGER ALAA-ELDEEN
article en
1 citations

Abstract

The computation of the solutions of differential equations (DEs) and integral equations (IEs) has noteworthy aspects due to the fact that these equations’ numerical or analytical solutions can yield applicable benefits in various realms of categories of engineering, physics, biology, and signal processing finance, among others. The pseudo-Galerkin method, as a numerical technique for approximating solutions to various types of differential and integral equations, merges the elements concerning the Galerkin method as well as the collocation methods, turning it into a hybrid mode of approach, providing versatility, efficiency, accuracy along with reduced complexity. Accordingly, this paper uses the pseudo-Galerkin method to solve linear and nonlinear differential equations depending on the monic of Chebyshev’s first derivatives as new basis functions through which new operational matrices for derivatives for the introduced basis function have been formed. In addition, a new linearization relation has been proved. Consequently, this relation and other relations have been used via the pseudo-Galerkin method to transform the given initial boundary value problems (IBVPs) into an algebraic system of equations. The error analysis study verifies the convergence of the proposed method. Finally, elements of accuracy, efficiency, and correctness are investigated by solving several numerical applications and real-life problems, including an environmental pollution model.

Fractals
University of Massachusetts Chan Medical School (US), Umm al-Qura University (SA), University of Tabuk (SA), Helwan University (EG)
Zero hunger
Openalex Percentile: Top 28%
Electromagnetic Simulation and Numerical Methods
0.73
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