A numerical framework based on fuzzy finite difference is presented for approximating triangular solutions of partial differential equations by considering the type $$[gH-p]-$$ differentiability. The triangle functions are expanded using full Taylor expansion to develop a new method. By gH-differentiability, we approximate derivatives with difference. In particular, propose this method solve no...

We study the qualitative behavior of the positive solutions of a second-order rational fuzzy difference equationwith initial conditions being positive fuzzy numbers, and parameters are positive fuzzy numbers. More precisely, we investigate existence of positive solutions, boundedness and persistence, and stability analysis of a second-order fuzzy rational difference equation. Some numerical exa...

in this paper, a  fuzzy numerical procedure for solving fuzzy linear volterra integro-differential equations of the second kind under strong  generalized differentiability is designed. unlike the existing numerical methods, we do not replace the original fuzzy equation by a $2times 2$ system ofcrisp equations, that is the main difference between our method  and other numerical methods.error ana...

In this paper variation of constants formula for the inhomogeneous fuzzy matrix difference system X(n + 1) = A(n)X(n) + F (n) is constructed by considering corresponding matrix difference inclusion Xβ(n+ 1) ∈ AβXβ(n) +Fβ(n), xβ(0) ∈ X0 β after presenting a procedure for solving the fuzzy difference equation by an example. Mathematics Subject Classification: 26E50, 34A12, 34A30

Difference equations have already been successfully applied in a number of sciences (for a detailed study of the theory of difference equations and their applications, see [1, 2, 7, 8, 11]. The problem of identifying, modeling, and solving a nonlinear difference equation concerning a real-world phenomenon from experimental input-output data, which is uncertain, incomplete, imprecise, or vague, ...