Bernstein computational algorithm for integro-differential equations

In this study, we introduce a computational algorithm for solving Integro-Differential Equations (IDEs) using Bernstein polynomials as basis functions. The algorithm approximates the solution by expressing it in terms of Bernstein polynomials and substituting this assumed solution into the IDE. Collocating the resulting equation at evenly spaced points yields a system of linear algebraic equations, which is solved via matrix inversion to find the Bernstein coefficients. These coefficients are then used to construct the approximate solution. Numerical examples demonstrate the method's accuracy and efficiency, highlighting its advantages in reducing computational effort.

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Publication Details

Journal
Partial Differential Equations in Applied Mathematics
Published
2024-08-30
DOI
https://doi.org/10.1016/j.padiff.2024.100897
Citations
1
Primary Topic
Iterative Methods for Nonlinear Equations
Type
article
Field-Weighted Citation Impact
0.73
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article

Bernstein computational algorithm for integro-differential equations

Abayomi Ayotunde Ayoade, Taiye Oyedepo, Ganiyu Ajileye
1 citations
Partial Differential Equations in Applied Mathematics
Iterative Methods for Nonlinear Equations
0.73
article

Bernstein computational algorithm for integro-differential equations

Abayomi Ayotunde Ayoade, Taiye Oyedepo, Ganiyu Ajileye
article en
1 citations

Abstract

In this study, we introduce a computational algorithm for solving Integro-Differential Equations (IDEs) using Bernstein polynomials as basis functions. The algorithm approximates the solution by expressing it in terms of Bernstein polynomials and substituting this assumed solution into the IDE. Collocating the resulting equation at evenly spaced points yields a system of linear algebraic equations, which is solved via matrix inversion to find the Bernstein coefficients. These coefficients are then used to construct the approximate solution. Numerical examples demonstrate the method's accuracy and efficiency, highlighting its advantages in reducing computational effort.

Partial Differential Equations in Applied MathematicsVol. 11
University of Nigeria (NG), University of Lagos (NG), Kwararafa University (NG)
Openalex Percentile: Top 32%
Iterative Methods for Nonlinear Equations
0.73
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Bernstein computational algorithm for integro-differential equations — Abayomi Ayotunde Ayoade, Taiye Oyedepo, et al. · Partial Differential Equations in Applied Mathematics (2024) | TGRS Research Map | TGRS