Author
Listed:
- Aaqib Iqbal
- Rashid Nawaz
- Hina Hina
- Abdulaziz Garba Ahmad
- Homan Emadifar
- Abdellatif Ben Makhlouf
Abstract
In this article, we explore the utilization of the Caputo derivative and the Riemann–Liouville (R–L) fractional integral to analyze the optimal auxiliary function method for approximating fractional nonlinear long waves. Approximate long wave equation with a distinct dispersion relation offers the most accurate description of shallow water wave properties. Various methods, including the Adomian decomposition technique, the variational iteration method, the optimum homotopy asymptotic method, and the new iterative technique, have been employed and compared to those obtained using the fractional-order approximate long wave equation. The results of our study indicate that the optimal auxiliary function method is highly successful and practically simple, achieving better and more rapid convergence after just one repetition. This method is recognized as an efficient approach, demonstrating high precision in solving intriguing and intricate problems. Furthermore, it proves to be more time and resource efficient than other relevant analytical techniques, leading to significant savings in both volume and time. Compared to the Adomian decomposition technique, the new iterative technique, the variational iteration method, and the optimum homotopy asymptotic method, the suggested technique is extremely accurate computationally. It is also easy to analyze and solve fractionally linked nonlinear complex phenomena that arise in science and technology. We present the numerical and graphical findings that support these conclusions.
Suggested Citation
Aaqib Iqbal & Rashid Nawaz & Hina Hina & Abdulaziz Garba Ahmad & Homan Emadifar & Abdellatif Ben Makhlouf, 2024.
"Utilizing the Optimal Auxiliary Function Method for the Approximation of a Nonlinear Long Wave System considering Caputo Fractional Order,"
Complexity, Hindawi, vol. 2024, pages 1-10, May.
Handle:
RePEc:hin:complx:8357221
DOI: 10.1155/2024/8357221
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