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Hamdy Abdel-Gawad
Hamdy Abdel-Gawad

Public Documents 2
Analytic Solutions of Fractal and Fractional Time Derivative- Burgers-Nagumo Equation
Hamdy Abdel-Gawad
Mohammad Tantawy

Hamdy Abdel-Gawad

and 3 more

January 30, 2024
The Nagumo equation describes a reaction-diffusion system in biology. Here, it is coupled to Burgers equation, via including convection, which is, namely; Burgers-Nagumo equation BNE. The first objective of this work is to present a theorem to reduce the different versions of the fractional time derivatives FTD to “non autonomous” ordinary ones, that is ordinary derivatives with time dependent coefficients. The second objective is to find the exact solutions of the fractal and fractional time derivative -BNE, that is to solve BNE with time dependent coefficient. On the other hand FTD can be transformed to BNE with constant coefficients via similarity transformations. The unified and extended unified method are used. Self-similar solutions are also obtained. It is found that significant fractal effects hold for smaller order derivatives. While significant fractional effects hold for higher-order derivatives. The solutions obtained show solitary, wrinkle soliton waves, with double kinks, undulated, or with spikes. Further It is shown that wrinkle soliton wave, with double kink configuration holds for smaller fractal order. While in the case of fractional derivative, this holds for higher orders.
An Approach to Solutions of Fractal and Fractional Time Derivative Fokker-Planck Equa...
Hamdy Abdel-Gawad

Hamdy Abdel-Gawad

March 02, 2020
Abstract An approach to find the exact solution of ordinary, fractal and fractional Fokker-Planck equation FPE, based on transforming it to a system of first-order PDEs, together with using the extended unified method, is presented. Reduction of the fractal and fractional derivatives to the classical on's with time-dependent coefficient is performed via similarity transformations. Some explicit solutions of the classical, fractal and fractional time derivative FPE, are obtained . It is shown that the solution of the FPE is mixed Gaussian's. It is worthy to mention that the mixture of Gaussians is a powerful tool in machine learning. Further,it is found that the friction coefficient plays a significant role in lowering the magnitude of the distribution function. While changing the order of the fractal and fraction time derivative has a slight effects and the mean and mean square of the velocity vary slowly.

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