In this paper, we study the concept of statistical convergence on L?fuzzy normed spaces. Then give a useful characterization for statistically convergent sequences. Furthermore, illustrate that our method is more general than usual

in this paper we intend to offer new numerical methods to solve the second-order fuzzy abel-volterraintegro-differential equations under the generalized $h$-differentiability. the existence and uniqueness of thesolution and convergence of the proposed methods are proved in details and the efficiency of the methods is illustrated through a numerical example.

In this paper, we define (λ, μ)statistical convergence and (λ, μ)-statistical Cauchy double sequences on intuitionistic fuzzy normed spaces (IFNS in short), where λ = (λn) and μ = (μm) be two non-decreasing sequences of positive real numbers such that each tending to ∞ and λn+1 ≤ λn +1, λ1 = 1; μm+1 ≤ μm + 1, μ1 = 1. We display example that shows our method of convergence is more general for do...

In this paper,  fuzzy convergence theory in the framework of $L$-convex spaces is introduced. Firstly, the concept of $L$-convex remote-neighborhood spaces is introduced and it is shown that the  resulting category is isomorphic to that of $L$-convex spaces. Secondly, by means of $L$-convex ideals, the notion of $L$-convergence spaces is introduced and it is proved that the  category of $L$-con...