The main purpose of this paper is to find fuzzy root of fuzzy polynomials (if exists) by using Newton-Raphson method. The proposed numerical method has capability to solve fuzzy polynomials as well as algebric ones. For this purpose, by using parametric form of fuzzy coefficients of fuzzy polynomial and Newton-Rphson method we can find its fuzzy roots.Finally, we illustrate our approach by numerical examples.

In the present paper the topic proposed in [4] is followed. We have used a numerical method for solving "Fuzzy differential inclusions" by Adomian Decomposition method (ADM). The method is illustrated by solving some linear and nonlinear fuzzy initial value problems.

A finite-volume code, based on the SIMPLEC algorithm, has been extended to cover compressible flows. The key element of the extension is the transformation of the pressure correction equation to an equation for density transport. This is done by introducing upwind density correction terms implicitly via an equation of state, which gives a hyperbolic nature to the original elliptic equation. To check the validity of the method and extended code, different cases, including flow in a converging-diverging nozzle, over a bump in a channel and over a cylinder are considered. The accuracy and convergence behavior, and the significance of density interpolation and use of accurate second-order approximation schemes, such as QUICK, van Leer and Minimum Gradient for convective terms, are pointed out. It is shown that the method and extended code satisfy the required features of a compressible flow solver. Furthermore, it is concluded that the use of central interpolation for density and upwinding density corrections, and use of the Minimum Gradient second-order scheme for convective terms, in the present method, make up the best combination from considered options.

In this paper, the numerical solution of an algebraic complex fuzzy equation of degree n, based on the parametric fuzzy numbers, is discussed. The unknown variable and right-hand side of the equation are considered as fuzzy complex numbers, whereas, the coefficients of the equation, are considered to be real crisp numbers. The given method is a numerical method and proposed based on the separation of the real and imaginary parts of the equation and using the parametric forms of the fuzzy numbers in the form of polynomials of degree at most m. In this case, a system of nonlinear equations is achieved. To get the solutions of the system, we used the Gauss-Newton iterative method. We also very brie y explain the conjugate of the solution of such equations. Finally, the efficiency and quality of the given method are tested by applying it to some numerical examples.