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Solving Fractional Generalized Fisher–Kolmogorov–Petrovsky–Piskunov’s Equation Using Compact‐Finite Different Methods Together with Spectral Collocation Algorithms

Author

Listed:
  • Maged Z. Youssef
  • M. M. Khader
  • Ibrahim Al-Dayel
  • W. E. Ahmed

Abstract

The main target of this work is presenting two efficient accurate algorithms for solving numerically one of the most important models in physics and engineering mathematics, Fisher–Kolmogorov–Petrovsky–Piskunov’s equation (Fisher‐KPP) with fractional order, where the derivative operator is defined and studied by the fractional derivative in the sense of Liouville–Caputo (LC). There are two main processes; in the first one, we use the compact finite difference technique (CFDT) to discretize the derivative operator and generate a semidiscrete time derivative and then implement the Vieta–Lucas spectral collocation method (VLSCM) to discretize the spatial fractional derivative. The presented approach helps us to transform the studied problem into a simple system of algebraic equations that can be easily resolved. Some theoretical studies are provided with their evidence to analyze the convergence and stability analysis of the presented algorithm. To test the accuracy and applicability of our presented algorithm a numerical simulation is given.

Suggested Citation

  • Maged Z. Youssef & M. M. Khader & Ibrahim Al-Dayel & W. E. Ahmed, 2022. "Solving Fractional Generalized Fisher–Kolmogorov–Petrovsky–Piskunov’s Equation Using Compact‐Finite Different Methods Together with Spectral Collocation Algorithms," Journal of Mathematics, John Wiley & Sons, vol. 2022(1).
  • Handle: RePEc:wly:jjmath:v:2022:y:2022:i:1:n:1901131
    DOI: 10.1155/2022/1901131
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    1. M. M. Khader & M. Adel, 2020. "Numerical and theoretical treatment based on the compact finite difference and spectral collocation algorithms of the space fractional-order Fisher’s equation," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 31(09), pages 1-13, September.
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