Modified Variational Iteration Method for the Numerical Solutions of some Non-Linear Fredholm Integro-Differential Equations of the Second Kind

This paper provides approximate solutions to some nonlinear Fredholm-Integro differential equations of the second kind by using a Modified Variational Iteration Method. Comparison of the approximate solutions of this method with other known methods shows that the Modified Variational Iteration scheme is more accurate, reliable and readily implemented. Citation: Aloko MD, Fenuga OJ, Okunuga SA (2017) Modified Variational Iteration Method for the Numerical Solutions of some Non-Linear Fredholm Integro-Differential Equations of the Second Kind. J Appl Computat Math 6: 370. doi: 10.4172/2168-9679.1000370


Introduction
Many researchers in engineering and physical sciences have used different numerical methods to solve Fredholms Integro-differential equations. Many of these numerical methods gave reliable and accurate solutions [1] applied multi-wavelet direct method for solving integro -differential equations; Ghasemi et al. [2] used Homotopy perturbation method to solve integrodifferential equations [3][4][5][6]. Maleknejad et al. [7] use integral mean value theorem II [8][9][10] adopted Bernstein collocation method find approximate solution in Fredholm Integrodifferential equation, and Jianhua et al. [4] used Hybrid Function Operational Matrix techniques in Solving Fredholm Integrodifferential Equations. Lakestani et al. used spline wavelets method to solve the integro-differential equations, Rashidinia and Tahmasebi. Used modified Taylor expansion Method in solving Fredholm intgrodifferential equations and Shahooth et al. use Bernstein Polynomials Method. In this paper, nonlinear Fredholm integro-differential equations of the second kind where solved by modified variational iteration method which uses few numbers of iterations. Numerical examples and graphical results will demonstrate the efficiency of the method and will be shown that the method is accurate and readily implemented compared to some existing methods.

Non-Linear Fredholm Integro-Differential Equations
Consider the general non-linear, second kind Fredholm Integro-Differential equations of the form: indicate the n-th derivatives of u(x), c k are constants that represent the initial conditions and F(u(t)) is non-linear. u(x), fi(x), assumed to be real and, 1 λ′ is real finite constants F, f i and k i are continuous functions and is the unknown function to be determined.

Derivation of Modified Variational Iteration Method
To illustrate the basic concepts of Modified Variational Iteration Method, we consider the differential equation: L, N are linear, nonlinear operators respectively and are the inhomogeneous term. The variational iteration method presents a correction functional for eqn. (2) in the form: λ a general Lagrange's multiplier, which can be identified optimally via variational theory, that is, integration by parts and by using a restricted variation.
Determining the Lagrange's multiplier, this can be identified optimally via integration by parts and by using a restricted variation. λ ξ ξ ξ λ ξ ξ λ ξ ξ λ ξ ξ ξ λ ξ ξ ξ λ ξ ξ λ ξ ξ λ ξ ξ λ ξ ξ ξ λ ξ ξ ξ λ ξ ξ λ ξ ξ λ ξ ξ λ ξ ξ λ ξ ξ ξ The generalized integration by parts is ... Noting that in this method may be a constant or a function, and is a restricted value that means it behaves as a constant, is considered as restricted variation, i.e., where is the variational derivative. The extremum condition of requires that and this yields the stationary conditions: The successive approximations u n+1 ,` 0 n ≥ of the solution u(x) will be readily obtained upon using selective function u n (x) The Non-linear term is expressed in a unique way that gives a better approximation than the Adomian polynomial, Bell polynomial, Orthogonal polynomial just to mention a few. Considering a special case of eqn. (1) as: Subject to the initial conditions u (r) (0)=c r where c r , r=0,1…(n-1) are real constant and k, m are integers with k ≤m≤n.
In solving the general nth-order nonlinear integro-differential equations, we consider the following general functional equation of the form:

Lu=f+N(u)
Where N is the Non-linear differential operator, f is a known analytical function, N(u n ) is the nonlinear operator which is decomposed as The recurrence relations are defined as Assume a series solution of the form: Apply L -1 to the recurrence relation for the determination of the components, the (n+1) th approximation of the exact solutions for the unknown functions u(x) is obtained as The solution is constructed as: ( ) The modified algorithms is formulated as

Example 1
Consider the first-order Fredholm integro-differential eqns. (2) and (15) With the initial conditions u(0)=0 and exact solution u(x)=x, the correction functional for eqn. (15) is constructed as And making the functional stationary and noting that, n u  is a restriction variation, 0 n u δ =


. To find the optimal λ(ξ) and calculate variation with respect to u n , we have the stationary Conditions by applying eqns. (4) and (5): The Lagrange multiplier can be identified as λ=-1 Consequently, we have the following approximations (Table 1) ( )

Example 2
Consider the following nonlinear system of third-order Fredholm integrodifferential equation (Table 2) . To find the optimal λ(ξ) and calculate variation with respect to u n , we have the stationary conditions by applying in eqns.
Consequently, we have the following approximations and errors presented in Table 2.

Conclusion
In this paper, numerical methods for approximating solution of   Non-linear Fredholm-integral differential equation of the second kind are considered by using the modified vibrational iteration (MVIM) and this: • Help to reduce some inherited problems and weakness associated with other method as outlined in literatures.
• Comparison of the approximate, exact solutions shows that MVIM is more an efficient tool and more practical for solving non-linear systems of integral-differential equations and plot confirm.
• It will now be possible to investigate the approximate solution of nonlinear applied problems, particularly of the nonlinear problems in dynamic model of a chemical reactor and the present method reduces the computational difficulty of other traditional methods and all the calculation are made simple.