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Article

A Note on Fractional Third-Order Partial Differential Equations and the Generalized Laplace Transform Decomposition Method

by
Hassan Eltayeb
* and
Diaa Eldin Elgezouli
Mathematics Department, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
*
Author to whom correspondence should be addressed.
Fractal Fract. 2024, 8(10), 602; https://doi.org/10.3390/fractalfract8100602
Submission received: 17 August 2024 / Revised: 4 October 2024 / Accepted: 8 October 2024 / Published: 15 October 2024

Abstract

:
This paper establishes a unique approach known as the multi-generalized Laplace transform decomposition method (MGLTDM) to solve linear and nonlinear dispersive KdV-type equations. This method combines the multi-generalized Laplace transform (MGLT) with the decomposition method (DM), and offers a strong procedure for handling complicated equations. To verify the applicability and validity of this method, some ideal problems of dispersive KDV-type equations are discussed and the outcoming approximate solutions are stated in sequential form. The results show that the MGLTDM is a dependable and powerful technique to deal with physical problems in diverse implementations.

1. Intordection

Fractional partial differential equations (FPDEs) are utilized to model various physical phenomena in several regions of sciences and engineering, for instance, fluid mechanics, mathematical chemistry, quantum mechanics, kinetics, and linear optics. In 1895, Korteweg and de Vries acquired a non-dimensionalized equation, which is called the KdV equation. This model is employed to examine the dispersive wave phenomena in many fluids of science and technology. The e Korteweg–de Vries (KdV) equation was first introduced in [1,2] to evolving small amplitude, long surface gravity waves propagating in a shallow channel of water. This equation has arisen in several other physical contexts including collision-free hydromagnetic waves, stratified interior waves, ion-acoustic waves, plasma physics, lattice dynamics, etc. The fractional forced Korteweg–de Vries (FF-KdV) equation was studied by exploiting the fractional natural decomposition method (FNDM) in [3]. The (1 + 1) and (2 + 1) dimensional KdV equations are solved by using two methods called the variational homotopy perturbation method and a classical finite-difference method [4]. The researchers in [5] implemented the Shehu transformation and the iterative transformation technique under the Atangana–Baleanu fractional derivative to find an analytical solution to fractional fuzzy third-order dispersive KdV problems. A time-fractional third-order dispersive partial differential equation has a significant consequence in the area of mathematical sciences. The Laplace domain decomposition method has been proposed in [6] for solving four different types of KdV equations. Numerous outcomes of the dispersive KdV equations of the third and fifth orders were examined in [7,8]. The numerical approximation solution of the nonlinear KDV equation is obtained by using the ADM in [9]. The authors in [10] have successfully applied the ADM to find the solution of a coupled modified KdV equation. The authors in [11] applied the fractional differential transform method (FDTM) and the modified fractional differential transform method (MFDTM) to solve fractional third-order dispersive partial differential equations in one- and higher-dimensional spaces, The researchers in [12] developed a three-level implicit method to solve linear and non-linear third-order dispersive partial differential equations, a new numerical method which is a combination of Sumudu transforms and the Homotopy analysis method is used to discuss time fractional third-order dispersive-type PDEs [13]. The authors in [14] studied the non-integer Burger’s equation, the non-integer Schrodinger equation, and the non-integer coupled Burger’s equation by using Laplace-type integral transform combined with Adomian’s method. Generalized Laplace transform was utilized to solve partial differential equations (PDEs) in [15]. The authors in [16] checked the applicable range of G α -transform to obtain solutions of ordinary differential equations with variable coefficients. The solution of Abel’s integral equation has been investigated by applying G α -transform in [17]. The authors in [18] examined the solution of third-order dispersive partial differential equations by applying Sumudu-Generalized Laplace transform decomposition.
The fundamental goal of this work is to establish a novel definition for generalized multi-variable Laplace transform. Additionally, we then display how this technique alters fractional partial derivatives, ultimately profiting from the multi-generalized Laplace transform decomposition method solving one and two-dimensional fractional dispersive Korteweg–de Vries (KdV) equations. This procedure provided more versatile means to gain the solution of difficult fractional differential equations and illuminates possible applications in several scientific and engineering domains.

2. Definitions and Ideas

Here, we offer some basic important definitions and terminologies associated wth fractional calculus and generalized multi-Laplace transform decomposition, which are helpful in this study. Generalized Laplace transform (GLT) of the function f ( t ) is denoted by G α in the subsequent definition.
Definition 1. 
If f ( t ) is an integrable function determined for all t 0 , its (GLT) G α is the integral defined by F s , and is defined by G α f ; hence
F s = G t f = s α 0 f t e t s d t ,
where, s C and α Z ; for more details, see [19].
Definition 2. 
The fractional derivative of f ( x 1 , t ) in the Caputo sense is denoted by
D t σ f ( x 1 , t ) = 1 Γ k σ 0 t t τ k σ 1 k f ( x 1 , τ ) τ k d τ , k 1 < σ < m , k f ( x 1 , t ) t k , f o r k = σ N
For more details, see [20,21,22,23].
In this work, the following notations are used:
G 2 = G x 1 G t , G 2 1 = G p 1 1 G s 1 , G 3 = G x 1 G x 2 G t , G 3 1 = G p 1 1 G p 2 1 G s 1 G 4 = G x 1 G x 2 G x 3 G t , G 4 1 = G p 1 1 G p 2 1 G p 3 1 G s 1 .
In the following definitions, we determine the double-G Laplace transform (DGLT) and triple-G Laplace transform (TGLT) as:
Definition 3 
([24]). The (DGLT) of the function f ( x 1 , t ) is identified as
G 2 f ( x 1 , t ) = F ( p 1 , s ) = p 1 α s α 0 0 e x 1 p 1 t s f ( x 1 , t ) d t d x 1 ,
where α Z , p 1 , s C and the symbol G 2 indicates the transform of x 1 and t, respectively, and the function F p 1 , s is denoted as the (DGLT) of the f x 1 , t .
The notable advantage of the double-G Laplace transform is that it is more general than the other transforms because we can generate the following transformations:
  • If we put α = 0 , s = 1 s and p 1 = 1 p 1 , we obtain double Laplace transform
    L x 1 L t f x 1 , t = F p 1 , s = 0 0 f x 1 , t e p 1 x 1 + s t d t d x 1 ,
  • If we put α = 0 ,   q 1 = 1 p 1 and replace s with ϖ , we obtain Laplace–Yang Transform
    L x 1 Y f x 1 , t = F p 1 , ϖ = 0 0 f x 1 , t e q 1 x 1 + t ϖ d t d x 1 ,
  • At α = 1 and replacing p 1 ,   s by u ,  v, respectively, we obtain double Sumudu Transform
    S x 1 S t f x 1 , t = F u , v = 1 u v 0 0 f x 1 , t e x 1 u + t v d t d x 1 .
Definition 4 
([24]). The inverse double-G Laplace transform (IDGLT) is given by
G 2 1 F p 1 , s = f x 1 , t = 1 2 π i 2 τ i τ + i ς i ς + i e 1 p 1 x 1 + 1 s t F p 1 , s d s d p 1 ,
where G 2 1 indicates (IDGLT).
Definition 5 
([25]). The (TGLT) of the function f ( x 1 , x 2 , t ) is defined as
F ( p 1 , p 2 , s ) = G x 1 G x 2 G t f x 1 , x 2 , t = s α p 1 α p 2 α 0 0 e ( x 1 p 1 + x 2 p 2 + t s ) f x 1 , x 2 , t d t d x 2 d x 1 ,
where G x 1 G x 2 G t indicates (TGLT) and the symbols p 1 , p 2 and s denote transforms of the variable x 1 , x 2 and t, respectively.
Definition 6 
([25]). The inverse triple-G Laplace transform (ITGLT)
G p 1 1 G p 2 1 G s 1 F p 1 , p 2 , s = f x 1 , x 2 , t = 1 2 π i 3 τ i τ + i ς i ς + i η i δ + i e x 1 p 1 + x 2 p 2 + t s F p 1 , p 2 , s d s d p 2 d p 1 ,
where G p 1 1 G p 2 1 G s 1 indicates (IGTLT).
The multi-G Laplace transform (MGLT) of the function f x 1 , x 2 , , x n , t is offered by
j = 1 n G x j G t f x 1 , x 2 , , x n , t = F p 1 , p 2 , , p n , s = s α p 1 α p 2 α p n α 0 0 0 e ( x 1 p 1 + x 2 p 2 + x n p n + t s ) f x 1 , x 2 , , x n , t d t d x 1 d x 2 d x n ,
where j = 1 , 2 , 3 , , so, the (MGLTs) of ψ x 1 , x 2 , , x n , t t are provided by
j = 1 n G x j G t f x 1 , x 2 , , x n , t t = F p 1 , p 2 , , p n , s s β s α β + 1 j = 1 n G x j f x 1 , x 2 , , x n , 0 , 0 < β 1 ,
in particular at n = 1 , 2 . the (DGLT) and (TGLT) of functions f x 1 , t t and f x 1 , x 2 , t t are provided by
G 2 β f x 1 , t t β = F p 1 , s s β s α β + 1 G x 1 f x 1 , 0 , 0 < β 1 ,
G 3 β f x 1 , x 2 , t t β = F p 1 , p 2 , s s 2 β s α 2 β + 1 G x 1 f x 1 , x 2 , 0 0 < β 1 .
where the symbols G 2 and G 3 indicate DGLT and TGLT, respectively. The following example is helpful for this study.
Example 1. 
The double- and triple-G Laplace transforms of the function f ( x 1 , x 2 ) = e i a x 1 + b x 2 and g ( x 1 , x 2 , x 3 ) = e i x 1 + 2 x 2 + 3 x 3 are given by
G 2 e i a x 1 + b x 2 = p 1 α + 1 p 2 α + 1 1 a p 1 i 1 b p 2 i = p 1 α + 1 p 2 α + 1 1 + a p 1 i 1 + b p 2 i 1 a p 1 i 1 b p 2 i 1 + a p 1 i 1 + b p 2 i = p 1 α + 1 p 2 α + 1 1 a b p 1 p 2 + p 1 α + 1 p 2 α + 1 a p 1 + b p 2 i 1 + a 2 p 1 2 1 + b 2 p 2 2 .
where G 2 = G x G y indicate double-G Laplace transform with respect to x and y, and consequently,
G 2 cos ( a x 1 + b x 2 ) = p 1 α + 1 p 2 α + 1 1 a b p 1 p 2 1 + a 2 p 1 2 1 + b 2 p 2 2 ,
G 2 sin ( a x 1 + b x 2 ) = p 1 α + 1 p 2 α + 1 a p 1 + b p 2 1 + a 2 p 1 2 1 + b 2 p 2 2 ,
and the triple-G Laplace transform of g ( x 1 , x 2 , x 3 ) = e i x 1 + 2 x 2 + 3 x 3 is given by
G 3 e i x 1 + 2 x 2 + 3 x 3 = p 1 α + 1 p 2 α + 1 p 3 α + 1 1 p 1 i 1 2 p 2 i 1 3 p 3 i = p 1 α + 1 p 2 α + 1 p 3 α + 1 1 + p 1 i 1 + 2 p 2 i 1 + 3 p 3 i 1 p 1 i 1 2 p 2 i 1 3 p 3 i 1 + p 1 i 1 + 2 p 2 i 1 + 3 p 3 i = p 1 α + 1 p 2 α + 1 p 3 α + 1 1 2 p 1 p 2 3 p 1 p 3 6 p 2 p 3 1 + p 1 2 1 + 4 p 2 2 1 + 9 p 3 2 + p 1 α + 1 p 2 α + 1 p 3 α + 1 p 1 + 2 p 2 + 3 p 3 6 p 1 p 2 p 3 i 1 + p 1 2 1 + 4 p 2 2 1 + 9 p 3 2 .
where G 3 indicates the triple-G Laplace transform with respect to x , y and z, and consequently,
G 3 cos ( x 1 + 2 x 2 + 3 x 3 ) = p 1 α + 1 p 2 α + 1 p 3 α + 1 1 2 p 1 p 2 3 p 1 p 3 6 p 2 p 3 1 + p 1 2 1 + 4 p 2 2 1 + 9 p 3 2 ,
and
G 3 sin ( x 1 + 2 x 2 + 3 x 3 ) = p 1 α + 1 p 2 α + 1 p 3 α + 1 p 1 + 2 p 2 + 3 p 3 6 p 1 p 2 p 3 1 + p 1 2 1 + 4 p 2 2 1 + 9 p 3 2 .

3. n + 1-Dimensional Fractional Dispersive KDV Equation and MGLTDM

In this article unit, we explain four problems of linear and nonlinear fractional dispersive PDEs of order three employing the generalized Laplace transform decomposition method.
The first problem:
Let us consider the following linear n + 1 -dimensional Kdv equation with the initial condition of
β ψ t β + a j = 1 n ψ x j + j = 1 n 3 ψ x j 3 = f ( x 1 , x 2 , , x n , t ) , t > 0 , 0 < β 1 ,
and
ψ ( x 1 , x 2 , , x n , 0 ) = f 1 ( x 1 , x 2 , , x n ) .
where ψ x 1 , x 2 , , x n are field variables, x 1 , x 2 , , x n R are space coordinates in the propagation direction of the field and t is a time. To study the solution of Equation (6) using the MGLTDM, the following steps are discussed:
Step 1: With the assistance of MGLT, Equation (6) becomes
j = 1 n G x j G t β ψ t β + j = 1 n G x j G t a j = 1 n ψ x j + j = 1 n 3 ψ x j 3 = j = 1 n G x j G t f ( x 1 , x 2 , , x n , t ) .
Step 2: Employing Equation (3), we get
Ψ p 1 , p 2 , , p n , s s β s α F 1 p 1 , p 2 , , p n s β 1 = j = 1 n G x j G t a j = 1 n ψ x j + j = 1 n 3 ψ x j 3 + F p 1 , p 2 , , p n , s ,
where F p 1 , p 2 , , p n , s and F 1 p 1 , p 2 , , p n are the (MGLT) for f x 1 , x 2 , , x n , t and f 1 x 1 , x 2 , , x n , respectively.
Step 3: Multiplying Equation (9) by s β , we get
Ψ p 1 , p 2 , , p n , s = s α + 1 F 1 p 1 , p 2 , , p n s β j = 1 n G x j G t a j = 1 n ψ x j + j = 1 n 3 ψ x j 3 + s β F p 1 , p 2 , , p n , s .
Step 4: Operating inverse multi-G Laplace transform for Equation (10),
ψ ( x 1 , x 2 , , x n , t ) = j = 1 n G p j 1 G s 1 s α + 1 F 1 p 1 , p 2 , , p n + j = 1 n G p j 1 G s 1 s β F p 1 , p 2 , , p n , s j = 1 n G p j 1 G s 1 s β j = 1 n G x j G t a j = 1 n ψ x j + j = 1 n 3 ψ x j 3 ,
Step 5: Using the ADM procedure for Equation (11), we get
m = 0 ψ m = j = 1 n G p j 1 G s 1 s α + 1 F 1 p 1 , p 2 , , p n + s β F p 1 , p 2 , , p n , s j = 1 n G p j 1 G s 1 s β j = 1 n G x j G t a j = 1 n m = 0 ψ m x j + j = 1 n m = 0 3 ψ m x j 3 ,
where
ψ 0 = j = 1 n G p j 1 G s 1 s α + 1 F 1 p 1 , p 2 , , p n + s β F p 1 , p 2 , , p n , s ,
and the remaining contents are denoted by
ψ m + 1 = j = 1 n G p j 1 G s 1 s β j = 1 n G x j G t a j = 1 n ψ m x j + j = 1 n 3 ψ m x j 3 .
The series solution of Equation (6) is given by
ψ = ψ 0 + ψ 1 + ψ 2 +
Suppose that the inverse exists for each term of Equations (13) and (14).
The second problem:
Let us consider the following linear one-dimensional Kdv equation with the initial condition of
β ψ t β + a ψ x 1 + 3 ψ x 1 3 = f ( x 1 , t ) , t > 0 , 0 < β 1 ,
and
ψ ( x 1 , 0 ) = f 1 ( x 1 ) .
where ψ x 1 is a field variable, x 1 R is a space coordinate in the propagation direction of the field and t is a time. In order to solve Equation (15) by utilizing the double-generalized Laplace transform decomposition method (DGLTDM), the next steps are needed:
Step 1: With the help of DGLT, Equation (15) becomes
G 2 β ψ t β + G 2 a ψ x 1 + 3 ψ x 1 3 = G 2 f ( x 1 , t ) .
Step 2: Utilizing Equation (4), we will get
1 s β Ψ p 1 , s s α s β 1 F 1 p 1 = G 2 a ψ x 1 + 3 ψ x 1 3 + F p 1 , s ,
where F 1 p 1 and F p 1 , s are the (GLT) and (DGLT) for f x 1 , 0 and f x 1 , t , respectively.
Step 3: Multiplying Equation (18) by s β , we can get
Ψ p 1 , s = s α + 1 F 1 p 1 s β G 2 a ψ x 1 + 3 ψ x 1 3 + s β F p 1 , s .
Step 4: Operating the IDGLT for Equation (19),
ψ x 1 , t = G 2 1 s α + 1 F 1 p 1 + s β F p 1 , s G 2 1 s β G 2 a ψ x 1 + 3 ψ x 1 3 .
Step 5: Employing the ADM procedure for Equation (11), we obtain
m = 0 ψ m = G 2 1 s α + 1 F 1 p 1 + s β F p 1 , s G 2 1 s β G 2 a m = 0 ψ m x 1 + m = 0 3 ψ m x 1 3 ,
here, m = 0 , 1 , 2 , 3 , , where
ψ 0 = G 2 1 s α + 1 F 1 p 1 + s β F p 1 , s ,
the remainder of the components are given by
ψ m + 1 = G 2 1 s β G 2 a ψ m x 1 + 3 ψ m x 1 3 ,
The series solution of Equation (15) is given by
ψ = ψ 0 + ψ 1 + ψ 2 +
In the following example, we apply the DGLTDM to get the solution of the fractional dispersive KdV equation:
Example 2 
([6]). The fractional dispersive KdV equation subject to the initial condition is considered as follows:
β ψ t β + 3 ψ x 1 3 = sin π x 1 sin t π 3 cos π x 1 cos t , x 1 , t > 0 , 0 < β 1
and
ψ ( x 1 , 0 ) = sin π x 1 .
Solution 1. 
By utilizing the DGLT of Equation (24) and using Equation (19), we get
Ψ p 1 , s = π p 1 α + 2 s α + 1 1 + p 1 2 π 2 s β G 2 3 ψ x 1 3 + s σ G 2 sin π x 1 sin t π 3 cos π x 1 cos t ,
applying the  sin t  and  cos t  series in the Equation (26), we have
Ψ p 1 , s = π p 1 α + 2 s α + 1 1 + p 1 2 π 2 s β G 2 3 ψ x 1 3 s β G 2 sin π x 1 t t 3 3 ! + t 5 5 ! s β G 2 π 3 cos π x 1 1 t 2 2 ! + t 4 4 ! ,
Ψ p 1 , s = π p 1 α + 2 s α + 1 1 + p 1 2 π 2 s β G 2 3 ψ x 1 3 π p 1 α + 2 1 + p 1 2 π 2 s β + α + 2 s β + α + 4 + s β + α + 6 π 3 p 1 α + 1 1 + p 1 2 π 2 s β + α + 1 s β + α + 3 + s β + α + 5 ,
by employing an 0IDGLT for the Equation (28) and using the ADM proceeding it, we get
m = 0 ψ m x 1 , t = sin π x 1 sin π x 1 t β + 1 Γ β + 2 t β + 3 Γ β + 4 + t β + 5 Γ β + 6 π 3 cos π x 1 t β Γ β + 1 t β + 2 Γ β + 3 + t β + 4 Γ β + 5 G 2 1 s β G 2 3 ψ x 1 3 ,
ψ 0 x 1 , t = sin π x 1 sin π x 1 t β + 1 Γ β + 2 t β + 3 Γ β + 4 + t β + 5 Γ β + 6 π 3 cos π x 1 t β Γ β + 1 t β + 2 Γ β + 3 + t β + 4 Γ β + 5 ,
and
ψ m + 1 x 1 , t = G 2 1 s β G 2 3 ψ m x 1 3 .
where  m 0 ,  the following first two terms are denoted by
ψ 1 x 1 , t = G 2 1 s β G 2 3 ψ 0 x 1 3 = G 2 1 s β G 2 π 3 cos π x 1 G 2 1 s β G 2 π 3 cos π x 1 t β + 1 Γ β + 2 t β + 3 Γ β + 4 + t β + 5 Γ β + 6 + G 2 1 s β G 2 π 6 sin π x 1 t β Γ β + 1 t β + 2 Γ β + 3 + t β + 4 Γ β + 5
thus,
ψ 1 x 1 , t = G 2 1 π 3 s α + β + 1 p 1 α + 1 1 + p 1 2 π 2 G 2 1 π 3 p 1 α + 1 1 + p 1 2 π 2 s α + 2 β + 2 s α + 2 β + 4 + s α + 2 β + 6 s α + 2 β + 8 + + G 2 1 π 4 p 1 α + 2 1 + p 1 2 π 2 s α + 2 β + 1 s α + 2 β + 3 + s α + 2 β + 5 s α + 2 β + 7 + ,
hence,
ψ 1 x 1 , t = π 3 t β Γ β + 1 cos π x 1 π 3 cos π x 1 t 2 β + 1 Γ 2 β + 2 t 2 β + 3 Γ 2 β + 4 + t 2 β + 5 Γ 2 β + 6 + π 6 sin π x 1 t 2 β Γ 2 β + 1 t 2 β + 2 Γ 2 β + 3 + t 2 β + 4 Γ 2 β + 5 ,
at  m = 1 ,  we have
ψ 2 x 1 , t = G 2 1 s β G 2 3 ψ 1 x 1 3 = G 2 1 s β G 2 π 6 t β Γ β + 1 sin π x 1 G 2 1 s β G 2 π 6 sin π x 1 t 2 β + 1 Γ 2 β + 2 t 2 β + 3 Γ 2 β + 4 + t 2 β + 5 Γ 2 β + 6 G 2 1 s β G 2 π 9 cos π x 1 t 2 β Γ 2 β + 1 t 2 β + 2 Γ 2 β + 3 + t 2 β + 4 Γ 2 β + 5 , ψ 2 x 1 , t = π 6 t 2 β Γ 2 β + 1 sin π x 1 + π 6 sin π x 1 × t 3 β + 1 Γ 3 β + 2 t 3 β + 3 Γ 3 β + 4 + t 3 β + 5 Γ 3 β + 6 + π 9 cos π x 1 t 3 β Γ 3 β + 1 t 3 β + 2 Γ 3 β + 3 + t 3 β + 4 Γ 3 β + 5 .
We examine, the approximate solution of Equation (24) as the following:
ψ x 1 , t = sin π x 1 sin π x 1 t β + 1 Γ β + 2 t β + 3 Γ β + 4 + t β + 5 Γ β + 6 π 3 cos π x 1 t β Γ β + 1 t β + 2 Γ β + 3 + t β + 4 Γ β + 5 + π 3 t β Γ β + 1 cos π x 1 π 3 cos π x 1 × t 2 β + 1 Γ 2 β + 2 t 2 β + 3 Γ 2 β + 4 + t 2 β + 5 Γ 2 β + 6 + π 6 sin π x 1 t 2 β Γ 2 β + 1 t 2 β + 2 Γ 2 β + 3 + t 2 β + 4 Γ 2 β + 5 π 6 t 2 β Γ 2 β + 1 sin π x 1 + π 6 sin π x 1 × t 3 β + 1 Γ 3 β + 2 t 3 β + 3 Γ 3 β + 4 + t 3 β + 5 Γ 3 β + 6 + π 9 cos π x 1 t 3 β Γ 3 β + 1 t 3 β + 2 Γ 3 β + 3 + t 3 β + 4 Γ 3 β + 5
Thus, the precise solution at  β = 1  is described by
ψ x , t = sin π x 1 sin π x 1 t 2 Γ 3 t 4 Γ 5 + t 6 Γ 7 π 3 cos π x 1 t Γ 2 t 3 Γ 4 + t σ 5 Γ 6 + π 3 t Γ 2 cos π x 1 π 3 cos π x 1 t 3 Γ 4 t 5 Γ 6 + t 7 Γ 8 + π 6 sin π x 1 t 2 Γ 3 t 4 Γ 5 + t 6 Γ 7 t 8 Γ 9 + π 6 t 2 Γ 3 sin π x 1 + π 6 sin π x 1 t 4 Γ 5 t 6 Γ 7 + t 8 Γ 9 + π 9 cos π x 1 t 3 Γ 4 t 5 Γ 6 + t 7 Γ 8 .
By simplifying,
ψ x 1 , t = sin π x 1 sin π x 1 t 2 Γ 3 t 4 Γ 5 + t 6 Γ 7 t 8 Γ 7 + = sin π x 1 1 t 2 Γ 3 + t 4 Γ 5 t 6 Γ 7 + t 8 Γ 7 ,
ψ x 1 , t = sin π x 1 cos t .
Figure 1a introduces a comparison between the exact solution and the obtained numerical solution of Equation (24). At t = 1 and β = 1 the exact solution is gained. By taking diverse values of β , such as ( β = 0.95 , β = 0.99 ), we get the approximate solutions. Figure 1b shows the plot of function ψ ( x 1 , t ) in two dimensions.
Table 1 shows the numerical solution for different values of β for the function ψ ( x 1 , t ) .
Table 1. Compression between exact and approximation solutions.
Table 1. Compression between exact and approximation solutions.
ExactThe MethodErrorThe MethodError
β = 1β = 0.95β = 0.99
00000
0.14120.13630.00490.13960.0016
0.26860.25920.00940.26550.0031
0.36970.35680.01290.36540.0043
0.43460.41940.01520.42960.0050
0.45700.44100.01590.45170.0053
0.43460.41940.01520.42960.0050
0.36970.35680.01290.36540.0043
0.26860.25920.00940.26550.0031
0.14120.13630.00490.13960.0016
0.00000.00000.00000.00000.0000
In the following, we plan some significant evidence about the triple-G Laplace transform decomposition method (TGLTDM) to solve the linear fractional dispersive PDE of order three.
The third problem:
Consider the following linear two-dimensional Kdv equation with the initial condition of
β ψ t β + a 3 ψ x 1 3 + b 3 ψ x 2 3 = f ( x 1 , x 2 , t ) , x 1 , x 2 , t > 0 , 0 < σ 1 ,
and
ψ ( x 1 , x 2 , 0 ) = f 1 ( x 1 , x 2 ) ,
where a and b are constant. To gain the solution of Equation (30), the triple-generalized Laplace transform decomposition method (TGLTDM) and the next steps are suggested:
Step 1: Upon utilizing TGLT for Equation (30) and DGLT for Equation (31), we get
G 3 β ψ t β + G 3 a 3 ψ x 1 3 + b 3 ψ x 2 3 = G 3 f ( x 1 , x 2 , t ) ,
where the symbols G 3 = G x 1 G x 2 G t denote TGLT.
Step 2: Implementing Equation (4), we obtain
1 s β Ψ p 1 , p 2 , s s α s β 1 F 1 p 1 , p 2 = G 3 a 3 ψ x 1 3 + b 3 ψ x 2 3 + F p 1 , p 2 , s ,
where F 1 p 1 , p 2 and F p 1 , p 2 , s are the DGLT and TGLT for f x 1 , x 2 , 0 and f x 1 , x 2 , t , respectively.
Step 3: By multiplying Equation (33) by s β , we have
Ψ p 1 , p 2 , s = s α + 1 F 1 p 1 , p 2 s β G 3 a 3 ψ x 1 3 + b 3 ψ x 2 3 + s β F p 1 , p 2 , s .
Step 4: Applying ITGLT for Equation (34), we obtain
ψ x 1 , x 2 , t = G 3 1 s α + 1 F 1 p 1 , p 2 + s β F p 1 , p 2 , s G 3 1 s β G 3 a 3 ψ x 1 3 + b 3 ψ x 2 3 ,
where the symbol G 3 1 indicates ITGLT.
Step 5: By employing the ADM for Equation (35),
m = 0 ψ m = G 3 1 s α + 1 F 1 p 1 , p 2 + s β F p 1 , p 2 , s G 3 1 s β G 3 a m = 0 3 ψ m x 1 3 + b n = 0 3 ψ m x 2 3 .
Then, we determine the recurrence connections as
ψ 0 = G 3 1 s α + 1 F 1 p 1 , p 2 + s β F p 1 , p 2 , s ,
and
ψ m + 1 = G 3 1 s β G 3 a m = 0 3 ψ m x 1 3 + b n = 0 3 ψ m x 2 3 ,
and the series solution is given by
ψ = ψ 0 + ψ 1 + ψ 2 +
Example 3. 
The time-fractional dispersive KdV equation is two dimensional with the initial condition accorded by
β ψ t β + 3 ψ x 1 3 + 3 ψ x 2 3 = sin x 1 + x 2 cos t 2 cos x 1 + x 2 sin t , x 1 , x 2 , t > 0 , 0 < β 1
and
ψ ( x 1 , x 2 , 0 ) = 0 .
Solution 2. 
With the assistance of Equations (37) and (38), we arrive at
ψ 0 = G 3 1 p 1 + p 2 p 1 α + 1 p 2 α + 1 1 + p 1 2 1 + p 2 2 s α + β + 1 s α + β + 3 + s α + β + 5 G 3 1 2 1 p 1 p 2 p 1 α + 1 p 2 α + 1 1 + p 1 2 1 + p 2 2 s α + β + 2 s α + β + 4 + s α + β + 6 ,
ψ m + 1 = G 3 1 s β G 3 3 ψ m x 1 3 + 3 ψ m x 2 3 ,
ψ 0 = sin x 1 + x 2 t β Γ β + 1 t β + 2 Γ β + 3 + t β + 4 Γ β + 5 2 cos x 1 + x 2 t β + 1 Γ β + 2 t β + 3 Γ β + 4 + t β + 5 Γ β + 6 ,
where  m 0 .  The rest terms are denoted by,
ψ 1 = G 3 1 s β G 3 3 ψ 0 x 1 3 + 3 ψ 0 x 2 3 = G 3 1 s β G 3 2 cos x 1 + x 2 Λ + 4 sin x 1 + x 2 Υ ,
where
Λ = t β Γ β + 1 t β + 2 Γ β + 3 + t β + 4 Γ β + 5 t β + 6 Γ β + 7 + , Υ = t β + 1 Γ β + 2 t β + 3 Γ β + 4 + t β + 5 Γ β + 6 t β + 7 Γ β + 8 + .
The first three terms are given by
ψ 1 = G 3 1 2 1 p 1 p 2 p 1 α + 1 p 2 α + 1 1 + p 1 2 1 + p 2 2 s α + 2 β + 1 s α + 2 β + 3 + s α + 2 β + 5 s α + 2 β + 7 + + G 3 1 2 p 1 + p 2 p 1 α + 1 p 2 α + 1 1 + p 1 2 1 + p 2 2 s α + 2 β + 2 s α + 2 β + 4 + s α + 2 β + 6 s α + 2 β + 8 + , = 2 cos x 1 + x 2 t 2 β Γ 2 β + 1 t 2 β + 2 Γ 2 β + 3 + t 2 β + 4 Γ 2 β + 5 t 2 β + 6 Γ 2 β + 7 + + 4 sin x 1 + x 2 t 2 β + 1 Γ 2 β + 2 t 2 β + 3 Γ 2 β + 4 + t 2 β + 5 Γ 2 β + 6 t 2 β + 7 Γ 2 β + 8 + ,
ψ 2 = G 3 1 s β G 3 3 ψ 1 x 1 3 + 3 ψ 1 x 2 3 = 4 sin x 1 + x 2 t 3 β Γ 3 β + 1 t 3 β + 2 Γ 3 β + 3 + t 3 β + 4 Γ 3 β + 5 t 3 β + 6 Γ 3 β + 7 + + 8 cos x 1 + x 2 t 3 β + 1 Γ 3 β + 2 t 3 β + 3 Γ 3 β + 4 + t 3 β + 5 Γ 3 β + 6 t 3 β + 7 Γ 3 β + 8 + ,
ψ 3 = G 3 1 s β G 3 3 ψ 2 x 1 3 + 3 ψ 2 x 2 3 = 8 cos x 1 + x 2 t 4 β Γ 4 β + 1 t 4 β + 2 Γ 4 β + 3 + t 4 β + 4 Γ 4 β + 5 t 4 β + 6 Γ 4 β + 7 + 16 sin x 1 + x 2 t 4 β + 1 Γ 4 β + 2 t 4 β + 3 Γ 4 β + 4 + t 4 β + 5 Γ 4 β + 6 t 4 β + 7 Γ 4 β + 8 + ,
and so on. By adding the above iterations, the solution becomes
ψ ( x 1 , x 2 , t ) = sin x 1 + x 2 t β Γ β + 1 t β + 2 Γ β + 3 + t β + 4 Γ β + 5 2 cos x 1 + x 2 t β + 1 Γ β + 2 t β + 3 Γ β + 4 + t β + 5 Γ β + 6 + 2 cos x 1 + x 2 t 2 β Γ 2 β + 1 t 2 β + 2 Γ 2 β + 3 + t 2 β + 4 Γ 2 β + 5 + 4 sin x 1 + x 2 t 2 β + 1 Γ 2 β + 2 t 2 β + 3 Γ 2 β + 4 + t 2 β + 5 Γ 2 β + 6 4 sin x 1 + x 2 t 3 β Γ 3 β + 1 t 3 β + 2 Γ 3 β + 3 + t 3 β + 4 Γ 3 β + 5 + 8 cos x 1 + x 2 t 3 β + 1 Γ 3 β + 2 t 3 β + 3 Γ 3 β + 4 + t 3 β + 5 Γ 3 β + 6 8 cos x 1 + x 2 t 4 β Γ 4 β + 1 t 4 β + 2 Γ 4 β + 3 + t 4 β + 4 Γ 4 β + 5 16 sin x 1 + x 2 t 4 β + 1 Γ 4 β + 2 t 4 β + 3 Γ 4 β + 4 + t 4 β + 5 Γ 4 β + 6 .
In the special case when  β = 1 , the solution of Equation (39) becomes
ψ ( x 1 , x 2 , t ) = sin x 1 + x 2 t Γ 2 t 3 Γ 4 + t 5 Γ 6 t 7 Γ 8 + , = sin x 1 + x 2 sin t .
Table 2 shows the numerical solution for different values of β for the function ψ ( x 1 , x 2 , t ) .
Table 2. Compression between exact and approximation solutions.
Table 2. Compression between exact and approximation solutions.
ExactThe MethodErrorThe MethodError
β = 1β = 0.95β = 0.99
00000
0.16720.16930.00210.16760.0004
0.32770.33180.00410.32860.0009
0.47510.48110.00590.47640.0013
0.60360.61120.00750.60520.0016
0.70810.71690.00880.71000.0019
0.78430.79410.00980.78640.0021
0.82920.83960.01040.83140.0022
0.84110.85160.01050.84330.0022
0.81950.82970.01020.82160.0022
0.76510.77470.00960.76720.0020
Figure 2a presents a comparison between the exact solution and the gained numerical solution of Equation (39); at t = 1 and β = 1 , the exact solution is obtained; by taking various values of β , such as ( β = 0.95 , β = 0.99 ), the approximate solution is acquired. Figure 2b shows the plot of function ψ ( x 1 , x 2 , t ) with x 2 = 0 in three-dimensions.
The fourth problem:
In this part, we offered the DGLTDM to solve the nonlinear one-dimensional fractional KDV equation.
Now, let us consider the nonlinear (1 + 1) dimensional fractional dispersive KDV equation having the initial condition determined by
β ψ t β + a 3 ψ x 1 3 + b ψ ψ x 1 = f ( x 1 , t ) ,
and
ψ x 1 , 0 = f 1 ( x 1 ) .
where f ( x 1 , t ) and f 1 ( x 1 ) are defined, a and b are constants. To get the solution of Equation (43) the past examination method is suggested as follows:
ψ x 1 , t = G 2 1 s α + 1 F 1 p 1 + s β F p 1 , s G 2 1 s β G 2 a 3 ψ x 1 3 + b ψ ψ x 1 ,
thus,
m = 0 ψ m = G 2 1 s α + 1 F 1 p 1 + s β F p 1 , s G 2 1 s β G 2 a m = 0 3 ψ m x 1 3 + b m = 0 ψ m ψ m x 1
where
ψ 0 = G 2 1 s α + 1 F 1 p 1 + s β F p 1 , s .
The other elements are accorded by
ψ m + 1 = G 2 1 s β G t a 3 ψ m x 1 3 + b A m ,
The Adomian polynomials A m for the nonlinear term F ( ψ ) can be evaluated by using the following expression:
A m = 1 m ! d m d λ m F ( i = 0 λ i ψ i ) λ = 0 , m = 0 , 1 , 2 , 3 ,
For more details, see [10], where A m = m = 0 ψ m ψ m x 1 is confirmed by
A 0 = ψ 0 ψ 0 x 1 A 1 = ψ 0 x 1 ψ 1 + ψ 0 ψ 1 x 1 A 2 = ψ 0 x 1 ψ 2 + ψ 0 ψ 2 x 1 + ψ 1 ψ 1 x 1 A 3 = ψ 0 x 1 ψ 3 + ψ 0 ψ 3 x 1 + ψ 1 x 1 ψ 2 + ψ 1 ψ 2 x 1 ,
hence, the approximate solution of Equation (43) is given by
ψ x 1 , t = ψ 0 + ψ 1 + ψ 2 + .
We suppose a = 1 , b = 2 and f x 1 , t = 0 . In Equation (43), we obtain the next example:
Example 4. 
Let the following non-linear one-dimensional fractional KDV equation have an initial condition defined by
β ψ t β + 3 ψ x 1 3 2 ψ ψ x 1 = 0 ,
ψ x 1 , 0 = x 1 .
Solution 3. 
By applying Equations (47) and (48), we can get
ψ 0 = x 1 ,
and all other components are created by
ψ m + 1 = G 2 1 s β G 2 3 ψ m x 1 3 + G 2 1 s β G 2 2 A m .
By replacing  m = 0  in Equation (53), we have
ψ 1 = G 2 1 s β G 2 3 ψ 0 x 1 3 + G 2 1 s β G 2 2 A 0 = G 2 1 s β G 2 0 + G 2 1 s β G 2 2 ψ 0 ψ 0 x 1 = G 2 1 G 2 1 2 x 1 = G 2 1 2 p α + 2 s β + α + 1 , ψ 1 x 1 , t = 2 x 1 t β Γ β + 1 ;
at  m = 1 ,
ψ 2 = G 2 1 s β G 2 3 ψ 1 x 1 3 + G 2 1 s β G 2 2 A 1 = 2 G 2 1 s β G 2 ψ 0 ψ 1 x + ψ 1 ψ 0 x = G 2 1 s β G 2 8 x 1 t β Γ β + 1 = G 2 1 8 p α + 2 s 2 β + α + 1 ψ 2 x , t = 8 x 1 t 2 β Γ 2 β + 1 ;
at  m = 2 ,
ψ 3 = G 2 1 s β G 2 3 ψ 1 x 1 3 + G 2 1 s β G 2 2 A 2 , = G 2 1 s β G 2 32 x 1 t 2 β Γ 2 β + 1 + 8 x t 2 β Γ β + 1 Γ β + 1 , = G 2 1 32 p α + 2 s 3 β + α + 1 + 8 p α + 2 s 3 β + α + 1 Γ 2 β + 1 Γ β + 1 Γ β + 1 , = 32 x 1 t 3 β Γ 3 β + 1 + 8 x 1 t 3 β Γ 2 β + 1 Γ β + 1 Γ β + 1 Γ 3 β + 1 ;
thus, the approximation solution of Equation (50) is displayed by
ψ = x 1 + 2 x 1 t β Γ β + 1 + 8 x t 2 β Γ 2 β + 1 + 32 x 1 t 3 β Γ 3 β + 1 + 8 x 1 t 3 β Γ 2 β + 1 Γ β + 1 Γ β + 1 Γ 3 β + 1 +
In the partcular case when  β = 1 , we get
ψ = x 1 + 2 x 1 t + 4 x 1 t 2 + 8 x 1 t 3 + = x 1 1 + 2 t + 2 t 2 + 2 t 3 + = x 1 1 2 t .
Table 3 shows the numerical solution for different values of β for the function ψ ( x 1 , t ) .
Table 3. Compression between exact and approximation solutions.
Table 3. Compression between exact and approximation solutions.
ExactThe MethodErrorThe MethodError
β = 1β = 0.95β = 0.99
00000
0.12480.12980.00500.12570.0009
0.24960.25950.00990.25140.0018
0.37440.38930.01490.37710.0027
0.49920.51900.01980.50280.0036
0.62400.64880.02480.62850.0045
0.74880.77850.02970.75420.0054
0.87360.90830.03470.87990.0063
0.99841.03800.03961.00560.0072
1.12321.16780.04461.13130.0081
1.24801.29750.04951.25710.0091
Figure 3a offers a comparison between the exact solution and the numerical solution of Equation (50); at t = 1 and β = 1 , we get the exact solution; by taking different values of β , such as ( β = 0.95 , β = 0.99 ), we gained the approximate solutions. Figure 3b shows the plot of function ψ ( x 1 , t ) in two-dimensions.
In the following example, we apply the quadruple-generalized Laplace transform decomposition method.
Example 5. 
Finally, the non-homogeneous fractional third-order dispersive partial differential equation in three dimensional space with the initial condition is defined:
β ψ t β + 3 ψ x 1 3 + 1 8 3 ψ x 2 3 + 1 27 3 ψ x 3 3 = 3 cos x 1 + 2 x 2 + 3 x 3 sin t + sin x 1 + 2 x 2 + 3 x 3 cos t ,
and
ψ x 1 , x 2 , x 3 , 0 = 0 .
Solution 4. 
By employing the preceding method for Equation (54), we get
m = 0 ψ m = G 4 1 3 p 1 α + 1 p 2 α + 1 p 3 α + 1 1 2 p 1 p 2 3 p 1 p 3 6 p 2 p 3 1 + p 1 2 1 + 4 p 2 2 1 + 9 p 3 2 s α + β + 2 s α + β + 4 + s α + β + 6 + G 4 1 p 1 α + 1 p 2 α + 1 p 3 α + 1 p 1 + 2 p 2 + 3 p 3 6 p 1 p 2 p 3 1 + p 1 2 1 + 4 p 2 2 1 + 9 p 3 2 s α + β + 1 s α + β + 3 + s α + β + 5 G 4 1 s β G 4 m = 0 3 ψ m x 1 3 + m = 0 1 8 3 ψ m x 2 3 + m = 0 1 27 3 ψ m x 3 3 .
By operating the inverse on the right side, one can get
m = 0 ψ m = 3 cos x 1 + 2 x 2 + 3 x 3 t β + 1 Γ β + 2 t β + 3 Γ β + 4 + t β + 5 Γ β + 6 + sin x 1 + 2 x 2 + 3 x 3 t β Γ β + 1 t β + 2 Γ β + 3 + t β + 4 Γ β + 5 G 4 1 s β G 4 m = 0 3 ψ m x 1 3 + m = 0 1 8 3 ψ m x 2 3 G 2 1 s β G 4 m = 0 3 ψ m x 3 3 .
The first component is denoted by
ψ 0 = 3 cos x 1 + 2 x 2 + 3 x 3 t β + 1 Γ β + 2 t β + 3 Γ β + 4 + t β + 5 Γ β + 6 + sin x 1 + 2 x 2 + 3 x 3 t β Γ β + 1 t β + 2 Γ β + 3 + t β + 4 Γ β + 5 .
The elements are offered by
ψ m + 1 = G 4 1 s β G 4 3 ψ m x 1 3 + 1 8 3 ψ m x 2 3 + 1 27 3 ψ m x 3 3 .
For  m = 0 , 1 , 2 , 3 , ,  at  m = 0 , Equation (59) becomes
ψ 1 = G 4 1 s β G 4 3 ψ 0 x 1 3 + 1 8 3 ψ 0 x 2 3 + 1 27 3 ψ 0 x 3 3 .
Hence,
ψ 1 = G 4 1 s β G 4 9 sin x 1 + 2 x 2 + 3 x 3 t β + 1 Γ β + 2 t β + 3 Γ β + 4 + t β + 5 Γ β + 6 + G 4 1 s β G 4 3 cos x 1 + 2 x 2 + 3 x 3 t β Γ β + 1 t β + 2 Γ β + 3 + t β + 4 Γ β + 5 , = G 4 1 9 p 1 α + 1 p 2 α + 1 p 3 α + 1 p 1 + 2 p 2 + 3 p 3 6 p 1 p 2 p 3 1 + p 1 2 1 + 4 p 2 2 1 + 9 p 3 2 s α + 2 β + 2 s α + 2 β + 4 + s α + 2 β + 6 + G 4 1 3 p 1 α + 1 p 2 α + 1 p 3 α + 1 1 2 p 1 p 2 3 p 1 p 3 6 p 2 p 3 1 + p 1 2 1 + 4 p 2 2 1 + 9 p 3 2 s α + 2 β + 1 s α + 2 β + 3 + s α + 2 β + 5 , ψ 1 = 9 sin x 1 + 2 x 2 + 3 x 3 t 2 β + 1 Γ 2 β + 2 t 2 β + 3 Γ 2 β + 4 β + t 2 β + 5 Γ 2 β + 6 + 3 cos x 1 + 2 x 2 + 3 x 3 t 2 β Γ 2 β + 1 t 2 β + 2 Γ 2 β + 3 + t 2 β + 4 Γ 2 β + 5 .
By substituting  m = 1 ,  in Equation (59), we have
ψ 2 = G 4 1 s β G 4 27 cos x 1 + 2 x 2 + 3 x 3 t 2 β + 1 Γ 2 β + 2 t 2 β + 3 Γ 2 β + 4 + t 2 β + 5 Γ 2 β + 6 G 4 1 s β G 4 9 sin x 1 + 2 x 2 + 3 x 3 t 2 β Γ 2 β + 1 t 2 β + 2 Γ 2 β + 3 + t 2 β + 4 Γ 2 β + 5 , = G 4 1 27 p 1 α + 1 p 2 α + 1 p 3 α + 1 1 2 p 1 p 2 3 p 1 p 3 6 p 2 p 3 1 + p 1 2 1 + 4 p 2 2 1 + 9 p 3 2 s α + 3 β + 2 s α + 3 β + 4 + s α + 3 β + 6 G 4 1 9 p 1 α + 1 p 2 α + 1 p 3 α + 1 p 1 + 2 p 2 + 3 p 3 6 p 1 p 2 p 3 1 + p 1 2 1 + 4 p 2 2 1 + 9 p 3 2 s α + 3 β + 1 s α + 3 β + 3 + s α + 3 β + 5 , ψ 2 = 27 cos x 1 + 2 x 2 + 3 x 3 t 3 β + 1 Γ 3 β + 2 t 3 β + 3 Γ 3 β + 4 β + t 3 β + 5 Γ 3 β + 6 9 sin x 1 + 2 x 2 + 3 x 3 t 3 β Γ 3 β + 1 t 3 β + 2 Γ 3 β + 3 + t 3 β + 4 Γ 3 β + 5 .
At  m = 2 , Equation (59) becomes
ψ 3 = G 4 1 s β G 4 81 sin x + 2 y + 3 z t 2 β + 1 Γ 2 β + 2 t 2 β + 3 Γ 2 β + 4 + t 2 β + 5 Γ 2 β + 6 G 4 1 s β G 4 27 cos x + 2 y + 3 z t 2 β Γ 2 β + 1 t 2 β + 2 Γ 2 β + 3 + t 2 β + 4 Γ 2 β + 5 , = G 4 1 81 p 1 α + 1 p 2 α + 1 p 3 α + 1 p 1 + 2 p 2 + 3 p 3 6 p 1 p 2 p 3 1 + p 1 2 1 + 4 p 2 2 1 + 9 p 3 2 s α + 3 β + 2 s α + 3 β + 4 + s α + 3 β + 6 G 4 1 27 p 1 α + 1 p 2 α + 1 p 3 α + 1 1 2 p 1 p 2 3 p 1 p 3 6 p 2 p 3 1 + p 1 2 1 + 4 p 2 2 1 + 9 p 3 2 s α + 3 β + 1 s α + 3 β + 3 + s α + 3 β + 5 , ψ 3 = 81 sin x 1 + 2 x 2 + 3 x 3 t 4 β + 1 Γ 4 β + 2 t 4 β + 3 Γ 4 β + 4 + t 4 β + 5 Γ 4 β + 6 27 cos x 1 + 2 x 2 + 3 x 3 t 4 β Γ 4 β + 1 t 4 β + 2 Γ 4 β + 3 + t 4 β + 4 Γ 4 β + 5 .
This easily yields the approximation solution as follows:
ψ x , y , z , t = 3 cos x 1 + 2 x 2 + 3 x 3 t β + 1 Γ β + 2 t β + 3 Γ β + 4 + t β + 5 Γ β + 6 + sin x 1 + 2 x 2 + 3 x 3 t β Γ β + 1 t β + 2 Γ β + 3 + t β + 4 Γ β + 5 + 9 sin x 1 + 2 x 2 + 3 x 3 t 2 β + 1 Γ 2 β + 2 t 2 β + 3 Γ 2 β + 4 + t 2 β + 5 Γ 2 β + 6 + 3 cos x 1 + 2 x 2 + 3 x 3 t 2 β Γ 2 β + 1 t 2 β + 2 Γ 2 β + 3 + t 2 β + 4 Γ 2 β + 5 + 27 cos x 1 + 2 x 2 + 3 x 3 t 3 β + 1 Γ 3 β + 2 t 3 β + 3 Γ 3 β + 4 + t 3 β + 5 Γ 3 β + 6 9 sin x 1 + 2 x 2 + 3 x 3 t 3 β Γ 3 β + 1 t 3 β + 2 Γ 3 β + 3 + t 3 β + 4 Γ 3 β + 5 81 sin x 1 + 2 x 2 + 3 x 3 t 4 β + 1 Γ 4 β + 2 t 4 β + 3 Γ 4 β + 4 + t 4 β + 5 Γ 4 β + 6 27 cos x 1 + 2 x 2 + 3 x 3 t 4 β Γ 4 β + 1 t 4 β + 2 Γ 4 β + 3 + t 4 β + 4 Γ 4 β + 5 .
The solution of Equation (54) is gained at  β = 1 ,  as follows:
ψ x 1 , x 2 , x 3 , t = sin x 1 + 2 x 2 + 3 x 3 t Γ 2 t 3 Γ 4 + t 5 Γ 6 t 7 Γ 8 + = sin x 1 + 2 x 2 + 3 x 3 sin t .
Figure 4a introduces a comparison between the exact solution and the numerical solution of Equation (54); at t = 1 and β = 1 the exact solution is obtained; by taking different values of β , such as ( β = 0.95 , β = 0.99 ), we get the approximate solutions. Figure 4b shows the plot of function ψ ( x 1 , x 2 , x 3 , t ) with x 2 = x 3 = 0 in four-dimensions.
Table 4 shows the numerical solution for different values of β for the function ψ ( x 1 , x 2 , x 3 , t ) .
Table 4. Compression between exact and approximation solutions.
Table 4. Compression between exact and approximation solutions.
ExactThe MethodErrorThe MethodError
β = 1β = 0.95β = 0.99
00000
0.01480.01630.00150.01530.0005
0.05360.05780.00420.05500.0014
0.09730.10360.00640.09940.0021
0.11610.12260.00650.11820.0021
0.07740.08120.00380.07870.0012
−0.0458−0.04780.0020−0.04650.0007
−0.2667−0.27680.0102−0.27000.0034
−0.5775−0.59700.0195−0.58400.0065
−0.9475−0.97590.0283−0.95690.0094
−1.3242−1.35900.0349−1.33570.0116

4. Conclusions

In this study, the solution of the fractional time dispersive Kdv equation was introduced utilizing the MGLTDM. This method is a combination of MGLT and the DM. We examined four examples to check the effectiveness and ability of our method, demonstrating its faculty to approximate solutions for different problems. In addition, the acheived results show that this method can handle many problems that existing methods cannot handle.

Author Contributions

Methodology, H.E.; Software, D.E.E.; Formal analysis, H.E.; Investigation, H.E.; Resources, H.E.; Data curation, D.E.E.; Writing—original draft, H.E.; Writing—review & editing, D.E.E. All authors have read and agreed to the published version of the manuscript.

Funding

The authors would like to extend their sincere appreciation to the Researchers Supporting Project number (RSPD2024R948), King Saud University, Riyadh, Saudi Arabia.

Data Availability Statement

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. (a): Comparison between exact and numerical solutions. (b): The surface of the function ψ ( x 1 , t ) .
Figure 1. (a): Comparison between exact and numerical solutions. (b): The surface of the function ψ ( x 1 , t ) .
Fractalfract 08 00602 g001
Figure 2. (a): A comparison between exact and numerical solutions. (b): The surface of the function ψ ( x 1 , t ) .
Figure 2. (a): A comparison between exact and numerical solutions. (b): The surface of the function ψ ( x 1 , t ) .
Fractalfract 08 00602 g002
Figure 3. (a): Comparison between exact and numerical solutions. (b): The surface of the function ψ ( x 1 , t ) .
Figure 3. (a): Comparison between exact and numerical solutions. (b): The surface of the function ψ ( x 1 , t ) .
Fractalfract 08 00602 g003
Figure 4. (a): Comparison between exact and numerical solutions. (b): The surface of the function ψ ( x 1 , t ) .
Figure 4. (a): Comparison between exact and numerical solutions. (b): The surface of the function ψ ( x 1 , t ) .
Fractalfract 08 00602 g004
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Eltayeb, H.; Elgezouli, D.E. A Note on Fractional Third-Order Partial Differential Equations and the Generalized Laplace Transform Decomposition Method. Fractal Fract. 2024, 8, 602. https://doi.org/10.3390/fractalfract8100602

AMA Style

Eltayeb H, Elgezouli DE. A Note on Fractional Third-Order Partial Differential Equations and the Generalized Laplace Transform Decomposition Method. Fractal and Fractional. 2024; 8(10):602. https://doi.org/10.3390/fractalfract8100602

Chicago/Turabian Style

Eltayeb, Hassan, and Diaa Eldin Elgezouli. 2024. "A Note on Fractional Third-Order Partial Differential Equations and the Generalized Laplace Transform Decomposition Method" Fractal and Fractional 8, no. 10: 602. https://doi.org/10.3390/fractalfract8100602

APA Style

Eltayeb, H., & Elgezouli, D. E. (2024). A Note on Fractional Third-Order Partial Differential Equations and the Generalized Laplace Transform Decomposition Method. Fractal and Fractional, 8(10), 602. https://doi.org/10.3390/fractalfract8100602

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