this paper intends to offer a new iterative method based on articial neural networks for finding solution of a fuzzy equations system. our proposed fuzzied neural network is a ve-layer feedback neural network that corresponding connection weights to output layer are fuzzy numbers. this architecture of articial neural networks, can get a real input vector and calculates its corresponding fu...

Several authors have proposed different methods to find the solution of fully fuzzy linear programming (FFLP) problems. But all the existing methods are based on the assumption that all the fuzzy coefficients and the fuzzy variables are non-negative fuzzy numbers. in this paper a new method is proposed to solve an FFLP problems with arbitrary fuzzy coefficients and arbitrary fuzzy variables, th...

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 non-negative fuzzy number vector x̃ which satisfies Ãx̃ = b̃, where à is a fuzzy number matrix. Then we investigate the existence of a positive solution of fully fuzzy linear system (...

in this paper we consider the problem of delay-dependent robusth1 control for uncertain fuzzy systems with time-varying delay. the takagi–sugeno (t–s) fuzzy model is used to describe such systems. time-delay isassumed to have lower and upper bounds. based on the lyapunov-krasovskiifunctional method, a sufficient condition for the existence of a robust $h_{infty}$controller is obtained. the fuzz...

We present a solution set description for systems of complex interval equations, where complex intervals have a rectangular form. The solution set is described by a system of nonlinear inequalities, which can be used to obtain a very accurate approximation of the interval hull of the solution set. In our numerical experiments we exploit this approximation to study overestimation for common comp...