In the paper, we present a new definition of fractional derivative with a smooth kernel which takes on two different representations for the temporal and spatial variable. The first works on the time variables; thus it is suitable to use the Laplace transform. The second definition is related to the spatial variables, by a non-local fractional derivative, for which it is more convenient to work...

In recent years, notable contributions have been made to both the theory and applications of the fractional differential equations. These equations are increasingly used to model problems in research areas as diverse as population dynamics, mechanical systems, fiber optics, control, chaos, fluid mechanics, continuous-time random walks, anomalous diffusive and subdiffusive systems, unification o...

The diffusion equations with the local and the nonlocal fractional derivatives have been used to describe the flow through disorder media. Recently, the variational iteration method is successfully developed to find approximate solutions of the two kinds of fractional differential equations. This study reveals the new development of the method and compares the applications in two types of fract...

This research work is dedicated to solving the n-generalized Korteweg–de Vries (KdV) equation in a fractional sense. The method combination of Sumudu transform and Adomian decomposition method. has significant advantages for differential equations that are both linear nonlinear. It easy find solutions fractional-order PDEs with less computing labor.

In this work, we investigate the dynamical behavior of a fractional order cholera model. All the feasible equilibria for the system are obtained and the conditions for the existence of interior equilibrium are determined. Local stability analysis of the cholera model is studied by using the fractional Routh-Hurwitz stability conditions. Our results indicate the potential of fractional-order cho...

In this paper, a new texture descriptor named "Fractional Local Neighborhood Intensity Pattern" (FLNIP) has been proposed for content based image retrieval (CBIR). It is an extension of the Local Neighborhood Intensity Pattern (LNIP)[1]. FLNIP calculates the relative intensity difference between a particular pixel and the center pixel of a 3×3 window by considering the relationship with adjacen...