Higher-order numeric Wazwaz–El-Sayed modified Adomian decomposition algorithms

Numerical Investigation of Higher Order Nonlinear Problem in the Calculus Of Variations Using Adomian Decomposition Method

In this paper, a numerical solution based on Adomian Decomposition Method (ADM) is used for finding the solution of higher order nonlinear problem which arise from the problems of calculus of variations. This approximation reduces the problem to an explicit system of algebraic equations. One numerical example is also given to illustrate the accuracy and applicability of the presented method.

Modified Adomian decomposition method for specific second order ordinary differential equations

In this paper, an efficient modification of Adomian decomposition method is introduced for solving second order ordinary differential equations. The proposed method can be applied to singular and nonsingular problems. The scheme is tested for some examples and the obtained results demonstrate efficiency of the proposed method. 2006 Elsevier Inc. All rights reserved.

Modified Adomian Decomposition Method for Double Singular Boundary Value Problems

where f(t),g(t), and h(t) are known continuous functions of t in the interval (0,1). Here N(u) is a nonlinear function of u. Let the above equation be singular at these two boundary value points t= 0,1. Scientists and engineers are interested in singular BVPs because they arise in a wide range of applications, such as in chemical engineering, mechanical engineering, nuclear industry, and nonlin...

Simulating fractional order systems using multistage Adomian decomposition method

Nonlinear phenomena play a crucial role in applied mathematics and physics. Analytic solutions of nonlinear equations are of fundamental importance and various methods for obtaining analytic solutions have been proposed. In this paper an application of the Adomian decomposition method is introduced for solving nonlinear fractional equations. The results reveal that the proposed method is very e...

Higher Order Dynamic Mode Decomposition