New Successive Approximation Methods for Solving Strongly Nonlinear Jaulent-Miodek Equations
2021-12
Scientific Journal of University of Zakho (Issue : 4) (Volume : 9)
In this paper, we propose two new techniques for solving system of nonlinear partial differential equations numerically, which we
first combine Laplace transformation method into a successive approximation method. Second, we combine Padé [2,2] technique
into the first proposed technique. To test the efficiency of our techniques, Jaulent-Miodek system was used, which contains partial
differential equations and has strongly nonlinear terms. Experimental results revealed that the first proposed technique gives better
results when the interval of t is small in terms of error approximation in tabular and graphical manners. Moreover, the results also
demonstrated that the second proposed technique gives better results regardless of the given interval of t in terms of the least square
errors.
Residual Power Series Method for Solving Klien - Gordon Schrodinger Equation
2021-06
SJUOZ (Issue : 2) (Volume : 9)
In this work, the residual power series method (RPSM) is used to find the approximate solution of Klien-Gordon Schrodinger (KGS) equation. furthermore, to show the accuracy and the efficiency of the presented method, we compare the obtained approximate solution of Klien-Gordon Schrodinger equation by residual power series method (RPSM) numerically and graphically with exact solution.
NUMERICAL COMPUTATION OF SUCCESSIVE APPROXIMATIONS METHOD AND VARIATIONAL ITERATION METHOD FOR SOLVING KLEIN-GORDON SCHRÖDINGER EQUATION
2021-04
J. Math. Comput. Sci. (Issue : 4) (Volume : 11)
This paper is devoted to investigating and comparing the Successive Approximations Method (SAM) and Variational Iteration Method (VIM) for solving Klein-Gordon Schrödinger (KGS) Equation. Furthermore, the approximate solutions that obtained by both methods have been represented numerically and graphically.
2020
Modified variational iteration and homotopy analysis method for solving variable coefficient variant boussinesq system
2020-02
General Letters in Mathematics (GLM) (Issue : 1) (Volume : 8)
In this paper, Modified Variational Iteration Method (MVIM) and Homotopy Analysis Method (HAM) are used to find approximate solutions for the Variable-Coefficient Variant Boussinesq System the (VCVB) system is able to describe the nonlinear and dispersive long gravity waves in shallow water traveling in two horizontal directions with varying depth, as an example we took the Boussinesq-Burgers (B-B) system, (B-B) system arise in the study of fluid flow and describing the long-wave propagation of shallow water waves. The solutions of these equations helpful for the coastal and civil engineering’s
2018
ADOMIAN AND ADOMIAN-PADÉ TECHNIQUE FOR SOLVING VARIABLE COEFFICIENT VARIANT BOUSSINESQ SYSTEM
2018-09
Science Journal of University of Zakho (Issue : 3) (Volume : 6)
In this paper, Adomian and Adomian-Padé Technique are used to find approximate solutions for the Variable-Coefficient Variant
Boussinesq System, and using Adomian-Padé Technique for Debug (Remove) The Gap (Complex Root).
2017
Successive approximation method for solving (1+1)-dimensional dispersive long wave equations
2017-07
International Journal of Advanced and Applied Sciences (Issue : 8) (Volume : 4)
In this paper, we study the (1+1)-dimensional dispersive long wave
equations which describe the evolution of horizontal velocity component
𝑢(𝑥, 𝑡) of water waves of height 𝑣(𝑥, 𝑡), and solved it numerically by
successive approximation method (SAM) to compare with Adomian’s
decomposition method (ADM), we found that SAM is suitable for this kind of
problems also its effective and more accure than ADM. Mathematica has been
Keywords: used for computation
2015
A New Analytical Study of Modified Camassa-Holm and Degasperis-Procesi Equations
2015-08
American Journal of Computational Mathematics (Issue : 5) (Volume : 5)
In this letter, variational homotopy perturbation method (VHPM) has been studied to obtain solitary
wave solutions of modified Camassa-Holm and Degasperis-Procesi equations. The results
show that the VHPM is suitable for solving nonlinear differential equations with fully nonlinear
dispersion term. The travelling wave solution for above equation compared with VIM, HPM, and
exact solution. Also, it was shown that the present method is effective, suitable, and reliable for
these types of equations.
Successive Approximation Method for Rayleigh Wave Equation
2015-05
IOSR Journal of Mathematics (Issue : 3) (Volume : 11)
In this paper, Rayleigh wave equation has been solved numerically for finding an approximate solution by Successive approximation method and Finite difference method. Example showed that Successive approximation method is much faster and effective for this kind of problems than Finite difference method.
Variational Homotopy Perturbation Method for Solving Benjamin-Bona-Mahony Equation
2015-04
Applied Mathematics (Issue : 6) (Volume : 6)
In this article, the application of variational homotopy perturbation method is applied to solve
Benjamin-Bona-Mahony equation. Then, we obtain the numerical solution of BBM equation using
the initial condition. Comparison with Adomian’s decomposition method, homotopy perturbation
method, and with the exact solution shows that VHPM is more effective and accurate than ADM
and HPM, and is reliable and manageable for this type of equation.
The Finite Difference Methods for Fitz Hugh-Nagumo Equation
2015-03
IOSR Journal of Mathematics (Issue : 2) (Volume : 11)
we have studied the numerical solutions for FitzHugh-Nagumo equation (FHN) using Finite Difference Methods (FDM) including explicit method, implicit (Crank-Nicholson) method, fully implicit method, Exponential method. A Comparison was made among all the methods by solving two numerical examples with different time steps.
2014
Adomain Decomposition Method for Solving Non Linear Partial Differential Equations
2014-09
IOSR Journal of Mathematics (Issue : 5) (Volume : 10)
In this paper, an application of A domain Decomposition method (ADM) is applied for finding the approximate solution of nonlinear partial differential equation. The results reveal that the A domain Decomposition method is very effective, simple and very close to the exact solution.
Solving the Kuramoto-Sivashinsky equation via Variational Iteration Method
2014-06
International Journal of Applied Mathematical Research (Issue : 3) (Volume : 3)
In this study, the approximate solutions for the Kuramoto-Sivashinsky equation by using the Variational Iteration Method (VIM) are obtained. Comparisons with the exact solutions and the solutions obtained by the Homotopy Perturbation Method (HPM), the numerical example show that the Variational Iteration Method (VIM) is accurate and effective and suitable for this kind of problem.
Homotopy analysis method for solving nonlinear diffusion equation with convection term
2014-04
International Journal of Applied Mathematical Research (Issue : 3) (Volume : 3)
In this article the homotopy analysis method (HAM) is used to find a numerical solution for the nonlinear diffusion equation with convection term. The numerical results obtained by using this method compared with the exact solution, by solving numerical example shows that (HAM) is accurate and close to the exact solution.
Numerical Solution of Nonlinear Diffusion Equation with Convection Term by Homotopy Perturbation Method
2014-01
IOSR Journal of Mathematics (Issue : 1) (Volume : 10)
In this paper, an application of homotopy perturbation method (HPM) is applied to finding the approximate solution of nonlinear diffusion equation with convection term, We obtained the numerically solution and compared with the exact solution.The results reveal that the homotopy perturbation method is very effective, simple and very close to the exact solution.
Adomian Decomposition Method for Solving the Kuramoto –Sivashinsky Equation
2014-01
IOSR Journal of Mathematics (Issue : 1) (Volume : 10)
The approximate solutions for the Kuramoto –Sivashinsky Equation are obtained by using the Adomian Decomposition method (ADM). The numerical example show that the approximate solution comparing with the exact solution is accurate and effective and suitable for this kind of problem.
2013
The Homotopy Perturbation Method for Solving the Kuramoto –Sivashinsky Equation
2013-12
IOSR Journal of Engineering (Issue : 12) (Volume : 3)
The approximate solutions for the Kuramoto –Sivashinsky Equation are obtained by using the homotopy perturbation method (HPM). The numerical example show that the approximate solution comparing with the exact solution is accurate and effective and suitable for this kind of problem.
Successive Approximation Method for Solving Nonlinear Diffusion Equation with Convection Term
2013-12
IOSR Journal of Engineerin (Issue : 12) (Volume : 3)
Nonlinear diffusion equation with convection term solved numerically using successive approximation method. Numerical example showed that (SAM) can solve this kind of models also comparing with the exact solution showed that SAM accurate and efficient method as shown in table (1) and Figures (1,2).
The Finite Difference Methods for –Nonlinear Klein Gordon Equation
2013-11
IOSR Journal of Engineering (Issue : 11) (Volume : 3)
Klein Gordon equation has been solved numerically by using fully implicit finite difference method (FIFDM) and exponential finite difference method (ExpFDM) and we found that both methods can solve this kind of problems, example showed that fully implicit method is more a accurate than exponential finite difference method.
Alternating direction explicit and implicit methods for Schnackenberg model
2013-09
International Journal of Engineering Research and Development (Issue : 7) (Volume : 8)
alternating direction explicit and alternating direction implicit methods (ADE and ADI) were used to solve Schnakenberg model, we were found that alternating direction implicit method is much more accurate and faster than alternating direction explicit in this kind of models.
Adomain Decomposition Method for ∅4 Klein Gordon Equationon
2013-08
International Journal of Engineering Inventions (Issue : 12) (Volume : 2)
∅ Klein Gordon Equation has been solved numerically by using two methods: finite difference method (FDM) and Adomain decomposition method (ADM) and we discover that the ADM is much more accurate than FDM in this kind of models as shown in the example(1,2).
The Finite Difference Methods And Its Stability For Glycolysis Model In Two Dimensions
2013-07
International Journal of Engineering Inventions (Issue : 11) (Volume : 2)
The Glycolysis Model Has Been Solved Numerically In Two Dimensions By Using Two Finite Differences Methods: Alternating Direction Explicit And Alternating Direction Implicit Methods (ADE And ADI) And We Were Found That The ADE Method Is Simpler While The ADI Method Is More Accurate. Also, We Found That ADE Method Is Conditionally Stable While ADI Method Is Unconditionally Stable. Keywords: Glycolysis Model, ADE Method, ADI Method.
2012
THE FINITE DIFFERENCE METHODS AND ITS STABILITY FOR GLYCOLYSIS MODEL IN ONE DIMENSION
The Glycolysis model has been solved numerically in one dimension by using two finite
dif ferences methods: explicit and C rank Nicolson method and we were found that the explicit method
is simpler while the Crank Nicolson is m ore accurate. Also, we found that explicit method is
conditionally stable while Crank Nicolson method is unconditionally stablestable.
2011
Numerical Stability of Brusselator System
2011-12
Raf. J. of Comp. & Math’s. (Issue : 2) (Volume : 8)
The numerical stability analysis of Brusselator system has been done in one and
two dimensional space. For one dimension we studied the numerical stability for
explicit and implicit (Crank- Nicolson) methods and we found that explicit method for
solving Brusselator system is stable under the conditionsr1<=(2-k(b+1)/8, r2<=1/2
While the implicit method is unconditionally stable. For two dimensional space we
found that ADE method is stable under condition r1<=(2-k(b+1)/8, r2<=1/4, while
ADI is unconditionally stable
Numerical Stability of Brusselator System
2011-03
AL-Rafidain Journal of Computer Sciences and Mathematics (Issue : 2) (Volume : 8)
The numerical stability analysis of Brusselator system has been done in one and two-dimensional space. For one dimension we studied the numerical stability for explicit and implicit (Crank- Nicolson) methods and we found that the explicit method for solving Brusselator system is stable under conditions, While the implicit method is unconditionally stable. For two-dimensional space, we found that ADE method is stable under conditions, while ADI is unconditionally stable.
2010
Numerical Solution of Brusselator Model by Finite Difference Method
2010-05
Journal of Applied Sciences Research (Issue : 11) (Volume : 6)
The Brusselator model has been solved numerically in one and two dimensions by using two
finite differences methods: For one dimension we used explicit and crank-Nicolson method and we were
found that the explicit method is simpler while the Crank-Nicolson is more accurate. For the two
dimensions we used the ADE and the ADI methods and we found that the ADI is more accurate than the
ADE.
Numerical Solutions and Stability Analysis of Brusselator System
2010-04
Noor Publishing (Issue : 1) (Volume : 1)
In this work, we studied the numerical solution of the Brusselator model in one dimension using FDM including explicit and implicit methods; FEM with weighted residual methods and iterative methods. Also, we studied the numerical solution of the Brusselator model in two dimensions using ADI ( Alternating Direction Implicit) and ADE (Alternating Direction Explicit) methods. Besides, we studied the numerical stability of FDM (explicit and implicit methods); the numerical stability analysis of the Brusselator system was done in one-dimensional space and two-dimensional spaces. For one dimensional space, we have studied the numerical stability for explicit and implicit (Crank- Nicolson) methods and we have found the stability condition for explicit method, whereas the implicit method is unconditionally stable. For two dimensional space, we found the stability condition for ADE method, while ADI is unconditionally stable.
Numerical Solution of Brusselator Model by Expansion Methods
2010-03
Australian Journal of Basic and Applied Sciences (Issue : 8) (Volume : 4)
In this paper, four types of weighted residual methods (Collocation, Subdomain, Galerkin and
least-square methods) are presented for finding an approximate solution of the Brusselator model.
We showed the efficiency of the prescribed methods by solving numerical example.
Numerical Solution of Brusselator Model by Finite Difference Method
2010-02
Journal of Applied Sciences Research (Issue : 11) (Volume : 6)
The Brusselator model has been solved numerically in one and two dimensions by using two
finite differences methods: For one dimension we used explicit and crank-Nicolson method and we were
found that the explicit method is simpler while the Crank-Nicolson is more accurate. For the two
dimensions we used the ADE and the ADI methods and we found that the ADI is more accurate than the
ADE.
Numerical Stability of Brusselator System
2010-02
Raf. J. of Comp. & Math’s (Issue : 2) (Volume : 8)
The numerical stability analysis of Brusselator system has been done in one and
two dimensional space. For one dimension we studied the numerical stability for
explicit and implicit (Crank- Nicolson) methods and we found that explicit method for
solving Brusselator system is stable under the conditions
4
2 ( 1)
1
- +
r £ k b , and 1/ 2. 2 r £
While the implicit method is unconditionally stable. For two dimensional space we
found that ADE method is stable under condition
8
2 ( 1)
1
r £ - k b + , and 1/ 4 2 r < , while
ADI is unconditionally stable.