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The Journal of Information and Optimization Sciences (JIOS) is a world leading journal publishing high quality, rigorously peer-reviewed original research in all mathematically-oriented theoretical and applied topics in information sciences, optimization sciences and related areas since 1980. Subjects include but are not limited to: • Information Sciences • Optimization Sciences • Control Theory • Operational Research • Decision Sciences • Information Theory • Information Technology • Computer Networks and Communications • Mathematical Programming • Modelling and Simulation • Database Management • Applications to Engineering Sciences • Applications to Technology

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Open Access Research Article

A novel approach based on the Muntz-Legendre polynomials for solving a class of the generalized Abel integral equations

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pp. 17–39Vol. 47Issue 1January 2026DOI: 10.47974/JIOS-1324XML
Received:
08 Mar 2022
Published Online:
01 Jan 2026
Article type:
Research Article
Language:
EN
Article no.:
JIOS-1324
Pages:
17–39

Abstract

This work is about a suitable numerical method based on the Muntz-Legendre polynomials for solving a type of the generalized Abel integral equations. The propose method approximates the unknown function with the Muntz-Legendre polynomials. To do this, we apply these functions and using Muntz-Galerkin method for the numerical solutions of this problem. Also, the stability and uniqueness of the solution by this scheme will be shown. Moreover, the convergence of this algorithm will be proved by preparing some theorems. Several numerical examples are presented to show the superiority and efficiency of current method.

Keywords

Subject Classifications

65M6065M1234A45

References

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