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Article

Approximating Multiple Roots of Applied Mathematical Problems Using Iterative Techniques

1
Mathematical Modelling and Applied Computation Research Group (MMAC), Department of Mathematics, King Abdulaziz University, P.O. Box 80203, Jeddah 21589, Saudi Arabia
2
Department of Mathematics, Guru Nanak Dev University, Amritsar 143005, India
3
Instituto Universitario de Matemática Multidisciplinar, Universitat Politècnica de València, 46022 València, Spain
*
Author to whom correspondence should be addressed.
Axioms 2023, 12(3), 270; https://doi.org/10.3390/axioms12030270
Submission received: 4 January 2023 / Revised: 8 February 2023 / Accepted: 23 February 2023 / Published: 6 March 2023
(This article belongs to the Special Issue Approximation Theory and Related Applications II)

Abstract

In this study, we suggest a new iterative family of iterative methods for approximating the roots with multiplicity in nonlinear equations. We found a lack in the approximation of multiple roots in the case that the nonlinear operator be non-differentiable. So, we present, in this paper, iterative methods that do not use the derivative of the non-linear operator in their iterative expression. With our new iterative technique, we find better numerical results of Planck’s radiation, Van Der Waals, Beam designing, and Isothermal continuous stirred tank reactor problems. Divided difference and weight function approaches are adopted for the construction of our schemes. The convergence order is studied thoroughly in the Theorems 1 and 2, for the case when multiplicity p2. The obtained numerical results illustrate the preferable outcomes as compared to the existing ones in terms of absolute residual errors, number of iterations, computational order of convergence (COC), and absolute error difference between two consecutive iterations.
Keywords: Steffensen’s method; nonlinear equations; optimal iterative methods; multiple roots Steffensen’s method; nonlinear equations; optimal iterative methods; multiple roots

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MDPI and ACS Style

Behl, R.; Arora, H.; Martínez, E.; Singh, T. Approximating Multiple Roots of Applied Mathematical Problems Using Iterative Techniques. Axioms 2023, 12, 270. https://doi.org/10.3390/axioms12030270

AMA Style

Behl R, Arora H, Martínez E, Singh T. Approximating Multiple Roots of Applied Mathematical Problems Using Iterative Techniques. Axioms. 2023; 12(3):270. https://doi.org/10.3390/axioms12030270

Chicago/Turabian Style

Behl, Ramandeep, Himani Arora, Eulalia Martínez, and Tajinder Singh. 2023. "Approximating Multiple Roots of Applied Mathematical Problems Using Iterative Techniques" Axioms 12, no. 3: 270. https://doi.org/10.3390/axioms12030270

APA Style

Behl, R., Arora, H., Martínez, E., & Singh, T. (2023). Approximating Multiple Roots of Applied Mathematical Problems Using Iterative Techniques. Axioms, 12(3), 270. https://doi.org/10.3390/axioms12030270

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