An optimal class of eighth-order iterative methods based on Kung and Traub's method with its dynamics
This work provides an incremental improvement in numerical analysis for solving nonlinear equations, offering a new optimal eighth-order method.
The authors propose an eighth-order iterative method for solving nonlinear equations that achieves optimal efficiency per the Kung-Traub conjecture, requiring only four function evaluations per iteration. Numerical tests show competitive accuracy and basin of attraction compared to existing methods.
In this paper, we present a three-point without memory iterative method based on Kung and Traub's method for solving non-linear equations in one variable. The proposed method has eighth-order convergence and costs only four function evaluations each iteration which supports the Kung-Traub conjecture on the optimal order of convergence. Consequently, this method possesses very high computational efficiency. We present the construction, the convergence analysis, and the numerical implementation of the method. Furthermore, comparisons with some other existing optimal eighth-order methods concerning accuracy and basins of attraction for several test problems will be given.