M. Othadi
Department of Mathematics, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran.
[ 1 ] - Numerical solution of hybrid fuzzy differential equations by fuzzy neural network
The hybrid fuzzy differential equations have a wide range of applications in science and engineering. We consider the problem of nding their numerical solutions by using a novel hybrid method based on fuzzy neural network. Here neural network is considered as a part of large eld called neural computing or soft computing. The proposed algorithm is illustrated by numerical examples and the result...
[ 2 ] - Solving fully fuzzy linear programming
In this paper, a new method is proposed to find the fuzzy optimal solution of fully fuzzy linear programming (abbreviated to FFLP) problems. Also, we employ linear programming (LP) with equality constraints to find a nonegative fuzzy number vector x which satisfies Ax =b, where A is a fuzzy number matrix. Then we investigate the existence of a positive solution of fully fuzzy linear system (FFLS).
[ 3 ] - Numerical solutions of nonlinear fuzzy Fredholm integro-differential equations of the second kind
In this paper, we use parametric form of fuzzy number, then aniterative approach for obtaining approximate solution for a classof nonlinear fuzzy Fredholmintegro-differential equation of the second kindis proposed. This paper presents a method based on Newton-Cotesmethods with positive coefficient. Then we obtain approximatesolution of the nonlinear fuzzy integro-differential equations by an it...
[ 4 ] - Minimal solution of fuzzy linear systems
In this paper, we use parametric form of fuzzy number and we converta fuzzy linear system to two linear system in crisp case. Conditions for the existence of a minimal solution to $mtimes n$ fuzzy linear equation systems are derived and a numerical procedure for calculating the minimal solution is designed. Numerical examples are presented to illustrate the proposed method.
[ 5 ] - Initial value problems for second order hybrid fuzzy differential equations
Usage of fuzzy differential equations (FDEs) is a natural way to model dynamical systems under possibilistic uncertainty. We consider second order hybrid fuzzy differentia
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