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Updating to Optimal Parametric Values by Memory-Dependent Methods: Iterative Schemes of Fractional Type for Solving Nonlinear Equations

Author

Listed:
  • Chein-Shan Liu

    (Center of Excellence for Ocean Engineering, National Taiwan Ocean University, Keelung 202301, Taiwan)

  • Chih-Wen Chang

    (Department of Mechanical Engineering, National United University, Miaoli 360302, Taiwan)

Abstract

In the paper, two nonlinear variants of the Newton method are developed for solving nonlinear equations. The derivative-free nonlinear fractional type of the one-step iterative scheme of a fourth-order convergence contains three parameters, whose optimal values are obtained by a memory-dependent updating method. Then, as the extensions of a one-step linear fractional type method, we explore the fractional types of two- and three-step iterative schemes, which possess sixth- and twelfth-order convergences when the parameters’ values are optimal; the efficiency indexes are 6 and 12 3 , respectively. An extra variable is supplemented into the second-degree Newton polynomial for the data interpolation of the two-step iterative scheme of fractional type, and a relaxation factor is accelerated by the memory-dependent method. Three memory-dependent updating methods are developed in the three-step iterative schemes of linear fractional type, whose performances are greatly strengthened. In the three-step iterative scheme, when the first step involves using the nonlinear fractional type model, the order of convergence is raised to sixteen. The efficiency index also increases to 16 3 , and a third-degree Newton polynomial is taken to update the values of optimal parameters.

Suggested Citation

  • Chein-Shan Liu & Chih-Wen Chang, 2024. "Updating to Optimal Parametric Values by Memory-Dependent Methods: Iterative Schemes of Fractional Type for Solving Nonlinear Equations," Mathematics, MDPI, vol. 12(7), pages 1-21, March.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:7:p:1032-:d:1367201
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    References listed on IDEAS

    as
    1. G Thangkhenpau & Sunil Panday & Shubham Kumar Mittal & Lorentz Jäntschi, 2023. "Novel Parametric Families of with and without Memory Iterative Methods for Multiple Roots of Nonlinear Equations," Mathematics, MDPI, vol. 11(9), pages 1-18, April.
    2. Chein-Shan Liu & Essam R. El-Zahar & Chih-Wen Chang, 2023. "Dynamical Optimal Values of Parameters in the SSOR, AOR, and SAOR Testing Using Poisson Linear Equations," Mathematics, MDPI, vol. 11(18), pages 1-21, September.
    3. T. Lotfi & F. Soleymani & Z. Noori & A. Kılıçman & F. Khaksar Haghani, 2014. "Efficient Iterative Methods with and without Memory Possessing High Efficiency Indices," Discrete Dynamics in Nature and Society, Hindawi, vol. 2014, pages 1-9, September.
    4. Muhammad Aslam Noor & Khalida Inayat Noor & Eisa Al-Said & Muhammad Waseem, 2010. "Some New Iterative Methods for Nonlinear Equations," Mathematical Problems in Engineering, Hindawi, vol. 2010, pages 1-12, January.
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