Numerical Solution of Integral Algebraic Equations with Singular Points Using the Least Squares Method

We conduct a numerical study of integral algebraic equations (IAEs) with singular points, which pose significant challenges for standard computational methods. The presence of singular points often renders classical discretization schemes unstable and inaccurate. This work explores the reformulation of such problems using a least squares framework to restore numerical stability. By recasting the singular IAE as a minimization problem, the least squares method effectively handles the non-integrability and ill-conditioning inherent in direct approaches. We provide a numerical analysis of the proposed scheme and present results from several test cases, demonstrating its superior performance in terms of the convergence rate and solution quality compared to conventional methods. Our findings establish the least squares method as a viable and effective tool for solving singular IAEs.

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Publication Details

Journal
Mathematics
Published
2026-02-16
DOI
https://doi.org/10.3390/math14040693
Primary Topic
Matrix Theory and Algorithms
Type
article
Field-Weighted Citation Impact
0.00

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article

Numerical Solution of Integral Algebraic Equations with Singular Points Using the Least Squares Method

V. F. Chistyakov, E. V. Chistyakova, Denis Nikolaevich Sidorov, Van Truong Vo et al.
Mathematics
Matrix Theory and Algorithms
article

Numerical Solution of Integral Algebraic Equations with Singular Points Using the Least Squares Method

V. F. Chistyakov, E. V. Chistyakova, Denis Nikolaevich Sidorov, Van Truong Vo, Aliona Dreglea
article en

Abstract

We conduct a numerical study of integral algebraic equations (IAEs) with singular points, which pose significant challenges for standard computational methods. The presence of singular points often renders classical discretization schemes unstable and inaccurate. This work explores the reformulation of such problems using a least squares framework to restore numerical stability. By recasting the singular IAE as a minimization problem, the least squares method effectively handles the non-integrability and ill-conditioning inherent in direct approaches. We provide a numerical analysis of the proposed scheme and present results from several test cases, demonstrating its superior performance in terms of the convergence rate and solution quality compared to conventional methods. Our findings establish the least squares method as a viable and effective tool for solving singular IAEs.

MathematicsVol. 14(4)
Harbin Institute of Technology (CN), Melentiev Energy Systems Institute (RU), Irkutsk National Research Technical University (RU), Institute for System Dynamics and Control Theory (RU)
Ministry of Science and Higher Education of the Russian Federation
Openalex Percentile: Top 52%
Matrix Theory and Algorithms
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