The main purpose of this article is to present an approximation method for solving Abel fuzzy integral equation in the most general form. The proposed approach is based on homotopy analysis method. This method transforms linear and nonlinear Abel fuzzy integral equations into two crisp linear and nonlinear integral equations. The convergence analysis for the proposed method is also introduced. We give some numerical applications to show efficiency and accuracy of the method. All of the numerical computations have been performed on a computer with the aid of a program written in Matlab
1 January 2015 in Journal of Taibah University for Science
In this paper, we study the numerical solution of hybrid fuzzy differential equations by using Adomian decomposition method (ADM). This is powerful method which consider the approximate solution of a nonlinear equation as an infinite series usually converging to the accurate solution. Several numerical examples are given and by comparing the numerical results obtained from ADM and predictor corrector method (PCM), we have studied their accuracy
1 March 2007 in Applied Mathematics and Computation
Numerical methods for solving integral equations have been the focus of much research, including reproducing kernel methods. We present a new algorithm to solve weakly singular Fredholm integral equations (WSFIEs). The advantage of this method is that it is possible to pick any point in the interval of integration and also the approximate solution. The advantage of this method is used to remove singularity and reproducing kernel functions are used as a basis. The convergence of approximation solution to the exact solution is also proved. Some examples are displayed to demonstrate that the method is accurate and efficient for WSFIEs.
1 January 2013 in Communications in Numerical Analysis
In this paper, we present a numerical method to solve the nonlinear Volterra-Fredholm integral equations by new basis functions (NFs). This is demonstrated by using a complementary pair of new orthogonal basis functions set (NFs) derived from the well-known block pulse functions set. Finally, we give some numerical examples, and the efficiency of this method will be shown by comparison with some numerical results.