Code and data for: A New Class of Optimal Fourth-Order Weight Functions for Solving Nonlinear Equations
Year: 2026
Type: dataset
Abstract: 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.
Source: Mendeley Data
DOI: 10.17632/vs6432tkdm
Author: Comemuang, Chalermwut
Language: English
Subfield: Numerical Analysis
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7210270918