this paper studies a new multi-objective fuzzy optimization prob- lem. the objective function of this study has dierent levels. therefore, a suitable optimized solution for this problem would be an optimized solution with preemptive priority. since, the feasible domain is non-convex; the tra- ditional methods cannot be applied. we study this problem and determine some special structures related...

In this paper, optimal control for stochastic linear singular Takagi–Sugeno (T–S) fuzzy delay system with quadratic performance is obtained using genetic programming (GP). To obtain the optimal control, the solution of matrix Riccati differential equation (MRDE) is computed by solving differential algebraic equation (DAE) using a novel and nontraditional GP approach. The GP solution is equivale...

In this paper, optimal control for stochastic linear quadratic singular neuro Takagi–Sugeno (T-S) fuzzy system with singular cost is obtained using genetic programming(GP). To obtain the optimal control, the solution of matrix Riccati differential equation (MRDE) is computed by solving differential algebraic equation (DAE) using a novel and nontraditional GP approach. The obtained solution in t...

In this work, we introduce a novel method for solving two-dimensional fuzzy Fredholm integral equations of the second kind (2D-FFIE-2). We use new representation of parametric form of fuzzy numbers and convert a two-dimensional fuzzy Fredholm integral equation to system of two-dimensional Fredholm integral equations of the second kind in crisp case. We can use Adomian decomposition method for n...

this paper presents the basic concepts of stability in fuzzy linguistic models. theauthors have proposed a criterion for bibo stability analysis of fuzzy linguistic modelsassociated to linear time invariant systems [25]-[28]. this paper presents the basic concepts ofstability in the general nonlinear and linear systems. this stability analysis method is verifiedusing a benchmark system analysis.

In this paper, a novel hybrid method based on learning algorithmof fuzzy neural network and Newton-Cotesmethods with positive coefficient for the solution of linear Fredholm integro-differential equation of the second kindwith fuzzy initial value is presented. Here neural network isconsidered as a part of large field called neural computing orsoft computing. We propose alearning algorithm from ...

Received 17 September 2011; revised 10 November 2011; accepted 17 November 2011. ———————————————————————————————Abstract In this paper, the fuzzy solution of non-linear fuzzy Volterra integro-differential equation (NFIDE) is approximated. To do this, we define a sequence of fuzzy functions which approximate the fuzzy solution of this type of equations and finally, we estimate upper bound of the...

in the present paper, we study some properties of fuzzy norm of linear operators. at first the bounded inverse theorem on fuzzy normed linear spaces is investigated. then, we prove hahn banach theorem, uniform boundedness theorem and closed graph theorem on fuzzy normed linear spaces. finally the set of all compact operators on these spaces is studied.

we present a new model and a new approach for solving fuzzylinear programming (flp) problems with various utilities for the satisfactionof the fuzzy constraints. the model, constructed as a multi-objective linearprogramming problem, provides flexibility for the decision maker (dm), andallows for the assignment of distinct weights to the constraints and the objectivefunction. the desired solutio...