Computational Analysis of Fractional-Order KdV Systems in the Sense of the Caputo Operator via a Novel Transform

Mashael M. AlBaidani, Abdul Hamid Ganie, Adnan Khan

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

The main features of scientific efforts in physics and engineering are the development of models for various physical issues and the development of solutions. In order to solve the time-fractional coupled Korteweg–De Vries (KdV) equation, we combine the novel Yang transform, the homotopy perturbation approach, and the Adomian decomposition method in the present investigation. KdV models are crucial because they can accurately represent a variety of physical problems, including thin-film flows and waves on shallow water surfaces. The fractional derivative is regarded in the Caputo meaning. These approaches apply straightforward steps through symbolic computation to provide a convergent series solution. Different nonlinear time-fractional KdV systems are used to test the effectiveness of the suggested techniques. The symmetry pattern is a fundamental feature of the KdV equations and the symmetrical aspect of the solution can be seen from the graphical representations. The numerical outcomes demonstrate that only a small number of terms are required to arrive at an approximation that is exact, efficient, and trustworthy. Additionally, the system’s approximative solution is illustrated graphically. The results show that these techniques are extremely effective, practically applicable for usage in such issues, and adaptable to other nonlinear issues.

Original languageEnglish
Article number812
JournalFractal and Fractional
Volume7
Issue number11
DOIs
StatePublished - Nov 2023

Keywords

  • Adomian decomposition method
  • Caputo operator
  • homotopy perturbation method
  • time-fractional coupled KdV equation
  • Yang transform

Fingerprint

Dive into the research topics of 'Computational Analysis of Fractional-Order KdV Systems in the Sense of the Caputo Operator via a Novel Transform'. Together they form a unique fingerprint.

Cite this