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Abstract and Applied Analysis

Volume 2013 (2013), Article ID 160681, 8 pages

http://dx.doi.org/10.1155/2013/160681

## Nonlinear Fractional Jaulent-Miodek and Whitham-Broer-Kaup Equations within Sumudu Transform

^{1}Institute for Groundwater Studies, Faculty of Natural and Agricultural Sciences, University of the Free State, Bloemfontein 9300, South Africa^{2}Department of Mathematics and Computer Sciences, Faculty of Art and Sciences, Cankaya University, Balgat, 06530 Ankara, Turkey^{3}Department of Chemical and Materials Engineering, Faculty of Engineering, King Abdulaziz University, P.O. Box 80204, Jeddah 21589, Saudi Arabia^{4}Institute of Space Sciences, P.O. Box MG-23, R 76900, Magurele-Bucharest, Romania

Received 15 April 2013; Accepted 28 April 2013

Academic Editor: Soheil Salahshour

Copyright © 2013 Abdon Atangana and Dumitru Baleanu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### Abstract

We solve the system of nonlinear fractional Jaulent-Miodek and Whitham-Broer-Kaup equations via the Sumudu transform homotopy method (STHPM). The method is easy to apply, accurate, and reliable.

#### 1. Introduction

Nonlinear partial differential equations arise in various areas of physics, mathematics, and engineering [1–4]. We notice that in fluid dynamics, the nonlinear evolution equations show up in the context of shallow water waves. Some of the commonly studied equations are the Korteweg-de Vries (KdV) equation, modified KdV equation, Boussinesq equation [5], Green-Naghdi equation, Gardeners equation, and Whitham-Broer-Kaup and Jaulent-Miodek (JM) equations. Analytical solutions of these equations are usually not available. Since only limited classes of equations are solved by analytical means, numerical solution of these nonlinear partial differential equations is of practical importance. Therefore, finding new methods and techniques to deal with these type of equations is still an open problem in this area. The purpose of this paper is to find an approximated solution for the system of fractional Jaulent-Miodek and Whitham-Broer-Kaup equations (FWBK) via the Sumudu transform method. The fractional systems of partial differential equations under investigation here are given below.

The nonlinear FWBK equation which will be considered in this paper has the following form: and the nonlinear FJM equation is The system of (1) and (2) is subjected to the following initial conditions: FWBK equation (1) describes the dispersive long wave in shallow water, where is the field of horizontal velocity, is the height which deviates from the equilibrium position of liquid, and and are constants that represent different powers. If and , (1) reduces to the classical long-wave equations which describe the shallow water wave with diffusion [6]. If and , (1) becomes the modified Boussinesq equations [7, 8]. FJM equation (2) appears in several areas of science such as condense matter physics [9], fluid mechanics [10], plasma physics [11], and optics [12] and associates with energy-dependent Schrödinger potential [13, 14].

The paper is organized as follows. In Section 2, we introduce briefly some of the basic tools of fractional order and of the Sumudu transform method. We show the numerical results in Section 4. The conclusions can be seen in Section 5.

#### 2. Basic Tools

##### 2.1. Properties and Definitions

*Definition 1 (see [15–24]). *A real function , , is said to be in the space , if there exists a real number , such that , where , and it is said to be in space if , .

*Definition 2 (see [15–24]). *The Riemann-Liouville fractional integral operator of order , of a function, , is defined as
Properties of the operator can be found in [15–23]; we mention only the following.

For , , and

*Definition 3. *The Caputo fractional order derivative is given as follows [15–18]:

*Definition 4. * The Riemann-Liouville fractional order derivative is given as follows [16–24]:

*Definition 5. * The Jumarie Fractional order derivative is given as follows [24]:

Lemma 6. *If , and , , then
*

*Definition 7 (partial derivatives of fractional order [15, 16, 19]). *Assume now that is a function of variables , also of class on . As an extension of Definition 3, we define partial derivative of order for with respect to the function
where is the usual partial derivative of integer order .

#### 3. Background of Sumudu Transform

*Definition 8 (see [25]). *The Sumudu transform of a function , defined for all real numbers , is the function , defined by

Theorem 9 (see [26]). *Let be the Sumudu transform of such that*(i)* is a meromorphic function, with singularities having ;*(ii)*there exist a circular region with radius and positive constants and with , then the function is given by
*

For the proof see [26].

##### 3.1. Basics of the Sumudu Transform Homotopy Perturbation Method

We illustrate the basic idea of this method [27–32] by considering a general fractional nonlinear nonhomogeneous partial differential equation with the initial condition of the following form: subject to the initial condition where denotes without loss of generality the Caputo fraction derivative operator, is a known function, is the general nonlinear fractional differential operator, and represents a linear fractional differential operator.

Applying the Sumudu transform on both sides of (10), we obtain Using the property of the Sumudu transform, we have Now applying the Sumudu inverse on both sides of (12) we obtain where represents the term arising from the known function and the initial conditions.

Now we apply the following HPM: The nonlinear term can be decomposed to using the He’s polynomial given as Substituting (15) and (16) gives which is the coupling of the Sumudu transform and the HPM using He’s polynomials. Comparing the coefficients of like powers of , the following approximations are obtained [29, 30]: Finally, we approximate the analytical solution by truncated series: The above series solutions generally converge very rapidly [29, 30].

#### 4. Applications

In this section, we apply this method for solving the system of the fractional differential equation. We will start with (1).

##### 4.1. Approximate Solution of (1)

Following carefully the steps involved in the STHPM, after comparing the terms of the same power of and choosing the appropriate initials conditions, we arrive at the following series solutions: And so on in the same manner one can obtain the rest of the components. However, here, few terms were computed and the asymptotic solution is given by Figures 1, 2, 3, and 4 show the graphical representation of the approximated solution of the system of nonlinear fractional Whitham-Broer-Kaup equation for , , , and .

##### 4.2. Approximate Solution of (2)

For (2), in the view of the Sumudu transform method, by choosing the appropriate initials conditions we are at the following series solutions: And so on in the same manner one can obtain the rest of the components. However, here, few terms were computed, and the asymptotic solution of the nonlinear fractional Jaulent-Miodek is given by Figures 5 and 6 show the graphical representation of the approximated solution of the system of nonlinear fractional Jaulent-Miodek equation for , , and . Figures 5 and 6 show the approximate solution of the main problem.

#### 5. Conclusion

We derived approximated solutions of nonlinear fractional Jaulent-Miodek and Whitham-Broer-Kaup equations using the relatively new analytical technique the STHPM. We presented the brief history and some properties of fractional derivative concept. It is demonstrated that STHPM is a powerful and efficient tool for the system of FPDEs. In addition, the calculations involved in STHPM are very simple and straightforward.

The STHPM is chosen to solve this nonlinear problem because of the following advantages that the method has over the existing methods. This method does not require the linearization or assumptions of weak nonlinearity. The solutions are not generated in the form of general solution as in the Adomian decomposition method (ADM) [33, 34]. No correction functional or Lagrange multiplier is required in the case of the variational iteration method [35, 36]. It is more realistic compared to the method of simplifying the physical problems. If the exact solution of the partial differential equation exists, the approximated solution via the method converges to the exact solution. STHPM provides us with a convenient way to control the convergence of approximation series without adapting , as in the case of [37] which is a fundamental qualitative difference in the analysis between STHPM and other methods. And also there is nothing like solving a partial differential equation after comparing the terms of same power of like in the case of homotopy perturbation method (HPM) [38].

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