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Highly accurate technique for studying some chaotic models described by ABC-fractional differential equations of variable-order

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  • M. M. Khader

    (Department of Mathematics and Statistics, College of Science, Imam Mohammad, Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia†Department of Mathematics, Faculty of Science, Benha University, Benha, Egypt)

  • Ibrahim Al-Dayel

    (Department of Mathematics and Statistics, College of Science, Imam Mohammad, Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia)

Abstract

The propose of this paper is to introduce and investigate a highly accurate technique for solving the fractional Logistic and Ricatti differential equations of variable-order. We consider these models with the most common nonsingular Atangana–Baleanu–Caputo (ABC) fractional derivative which depends on the Mittag–Leffler kernel. The proposed numerical technique is based upon the fundamental theorem of the fractional calculus as well as the Lagrange polynomial interpolation. We satisfy the efficiency and the accuracy of the given procedure; and study the effect of the variation of the fractional-order α(t) on the behavior of the solutions due to the presence of ABC-operator by evaluating the solution with different values of α(t). The results show that the given procedure is an easy and efficient tool to investigate the solution for such models. We compare the numerical solutions with the exact solution, thereby showing excellent agreement which we have found by applying the ABC-derivatives. We observe the chaotic solutions with some fractional-variable-order functions.

Suggested Citation

  • M. M. Khader & Ibrahim Al-Dayel, 2021. "Highly accurate technique for studying some chaotic models described by ABC-fractional differential equations of variable-order," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 32(02), pages 1-9, February.
  • Handle: RePEc:wsi:ijmpcx:v:32:y:2021:i:02:n:s0129183121500182
    DOI: 10.1142/S0129183121500182
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