In this paper, a new approach to determine the numerical solution of two-dimensional fuzzy Fredholm integral equation of the second kind (2DFFIE2) is proposed. This method is based on the fuzzy bivariate Bernstein polynomials. By using fuzzy bivariate Bernstein polynomials, a 2DFFIE2 can be transformed to a dual fuzzy linear system. The error estimate of this method is presented in terms of the...

In this article we found the solution of fuzzy linear controlled systemwith fuzzy initial conditions by using -cuts and presentation of numbersin a more compact form by moving to the eld of complex numbers. Next, afuzzy optimal control problem for a fuzzy system is considered to optimize theexpected value of a fuzzy objective function. Based on Pontryagin MaximumPrinciple, a constructive equati...

This paper mainly intends to discuss the solution of fully fuzzy linear systems (FFLS) Ax + b = Cx + d, where A and C are fuzzy matrices, b and d are fuzzy vectors. We transform the systems by using fuzzy numbers with a new parametric form for finding a fuzzy vector x that satisfies in the system.

In this paper, we present a method for solving the rst kind Abel integral equation. In thismethod, the rst kind Abel integral equation is transformed to the second kind Volterraintegral equation with a continuous kernel and a smooth deriving term expressed by weaklysingular integrals. By using Sidi's sinm - transformation and modied Navot-Simpson'sintegration rule, an algorithm for solving this...

Many of nonlinear systems in the field of engineering such as nano-resonator and atomic force microscope can be modeled based on Duffing equation. Analytical frequency response of this system helps us analyze different interesting nonlinear behaviors appearing in its response due to its rich dynamics. In this paper, the general form of Duffing equation with cubic nonlinearity as well as par...

Multivariate control chats are generally used in situations where the simultaneous monitoring or control of two or more related quality characteristics is necessary. In most processes in the real world, distribution of the process characteristics are unknown or at least non-normal, so the non-parametric or distribution-free charts are desirable. Most non-parametric statistical process-control t...