Code and data for: A New Class of Optimal Fourth-Order Weight Functions for Solving Nonlinear Equations

Description

This dataset contains the complete Python source code used to derive, verify, and generate every symbolic result, numerical table, and figure in the manuscript "A New Class of Optimal Fourth-Order Weight Functions for Solving Nonlinear Equations: Error Analysis, Singularity Dynamics, and Engineering Applications" (Chalermwut Comemuang, Buriram Rajabhat University). The package includes: (1) symbolic verification (SymPy) of the convergence theorem and its fifth-order refinement; (2) 1500-digit-precision (mpmath) numerical benchmarks of the three proposed weight-function methods against Newton-Raphson, Ostrowski, and eight recent literature methods (King, Chun et al., Zein, Abu Ghalioun & Zein) across six test functions; (3) complex-dynamics code (extraneous fixed points, critical points, attraction-basin generation) for three test polynomials of different degree and root symmetry; (4) engineering application solvers (CSTR, Casson fluid flow, diode-resistor circuit); and (5) a parameter-sensitivity sweep supporting the paper's choice of parameter values. A README.md details which script reproduces which table/figure in the manuscript and its Supplementary Material. All code is provided for independent reproduction of the paper's results.

Institutions

• Buriram Rajabhat University

  Buriram, Buriram

Categories

Licence