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September 10, 2025European Journal of Pure and Applied Mathematics1 citationsOpen Access

Advanced Mathematical Approaches for Solving Fractional-Order Korteweg-de Vries Equations

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NINaveed IqbalSHShah HussainAHAmjad E. Hamza

Key Points

  • The newly introduced methods outperform traditional techniques in solving fractional-order KdV equations, enhancing accuracy.
  • Using numerical data, the residual power series natural transform method significantly improves speed of convergence and precision.
  • The new iteration natural transform method offers reliable results in tackling nonlinear wave problems effectively.
  • Applying both techniques reveals opportunities to advance fractional calculus applications in fluid dynamics and plasma physics.

Abstract

In this work, we investigate the use of two new methods, residual power series natural transform method (RPSNTM) and new iteration natural transform method (NINTM), to tackle the fractional-order Korteweg-de Vries (KdV) equation. Many wave effects in fluid dynamics, plasma physics and traffic flow are described with the help of the fractional-order KdV equation. Tradi-tional techniques used to solve equations generally are not adapted to deal with the complications caused by fractional derivatives. The RPSNTM is presented as a valuable method to approximate how the solution will change with time by converting the problem into a step-by-step series. The NINTM is also used to make the solution more effective and reliable gradually. Applying both approaches offers a strong way to find approximate analytical answers to the KdV fractional-orderequation. Numerical data is used to reveal that the presented methods work better and faster than existing methods in terms of precision and speed of convergence. These results create new opportunities to apply fractional calculus in analyzing nonlinear waves.preparation.

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Cite This Study

Iqbal et al. (2025) studied this question.

synapsesocial.com/papers/68c1a77a54b1d3bfb60e0b95https://doi.org/10.29020/nybg.ejpam.v18i3.6316
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