Enhanced Ninth-Order Memory-Based Iterative Technique for Efficiently Solving Nonlinear Equations

In this article, we present a novel three-step with-memory iterative method for solving nonlinear equations. We have improved the convergence order of a well-known optimal eighth-order iterative method by converting it into a with-memory version. The Hermite interpolating polynomial is utilized to compute a self-accelerating parameter that improves the convergence order. The proposed uni-parametric with-memory iterative method improves its R-order of convergence from 8 to 8.8989. Additionally, no more function evaluations are required to achieve this improvement in convergence order. Furthermore, the efficiency index has increased from 1.6818 to 1.7272. The proposed method is shown to be more effective than some well-known existing methods, as shown by extensive numerical testing on a variety of problems.

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Publication Details

Journal
Mathematics
Published
2024-11-08
DOI
https://doi.org/10.3390/math12223490
Citations
3
Primary Topic
Iterative Methods for Nonlinear Equations
Type
article
Field-Weighted Citation Impact
2.20
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article

Enhanced Ninth-Order Memory-Based Iterative Technique for Efficiently Solving Nonlinear Equations

Lorentz Jäntschi, Shubham Kumar Mittal, Sunil Panday
3 citations
Mathematics
Iterative Methods for Nonlinear Equations
2.20
article

Enhanced Ninth-Order Memory-Based Iterative Technique for Efficiently Solving Nonlinear Equations

Lorentz Jäntschi, Shubham Kumar Mittal, Sunil Panday
article en
3 citations

Abstract

In this article, we present a novel three-step with-memory iterative method for solving nonlinear equations. We have improved the convergence order of a well-known optimal eighth-order iterative method by converting it into a with-memory version. The Hermite interpolating polynomial is utilized to compute a self-accelerating parameter that improves the convergence order. The proposed uni-parametric with-memory iterative method improves its R-order of convergence from 8 to 8.8989. Additionally, no more function evaluations are required to achieve this improvement in convergence order. Furthermore, the efficiency index has increased from 1.6818 to 1.7272. The proposed method is shown to be more effective than some well-known existing methods, as shown by extensive numerical testing on a variety of problems.

MathematicsVol. 12(22)
Technical University of Cluj-Napoca (RO), National Institute of Technology Manipur (IN)
Openalex Percentile: Top 12%
Iterative Methods for Nonlinear Equations
2.20
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