In this paper, we interpret a fuzzy differential equation by using the strongly generalized differentiability concept. Utilizing the Generalized characterization Theorem. Then a novel hybrid method based on learning algorithm of fuzzy neural network for the solution of differential equation with fuzzy initial value is presented. Here neural network is considered as a part of large eld called ne...

The convergence theory not only is an significantly basic theory of fuzzy topology and fuzzy analysis but also has wide applications in fuzzy inference and some other aspects. In this paper, we introduce the concept of α-generalized-remoteneighborhood of fuzzy points and establish the Moore-Smith α-generalized-convergence theory of L-fuzzy nets. Then, we introduce and study the concept of L-fuz...

In this paper, we present a new method for fuzzy risk analysis based on ranking generalized fuzzy numbers with different heights and different spreads. First, we present a new method for ranking generalized fuzzy numbers. The proposed method considers the defuzzified values, the heights and the spreads for ranking generalized fuzzy numbers. Based on the proposed method for ranking generalized f...

A few Karush-Kuhn-Tucker type of sufficient optimality conditions are given in this paper for nonsmooth continuous-time nonlinear multi-objective optimization problems in the Banach space L∞ [0, T ] of all n-dimensional vector-valued Lebesgue measurable functions which are essentially bounded, using Clarke regularity and generalized convexity. Further, we establish duality theorems for Wolfe an...

In this paper we have introduced the intuitionistic fuzzy generalized semi-pre connected space, intuitionistic fuzzy generalized semipre super connected space and intuitionistic fuzzy generalized semi-pre extremally disconnected space. We investigated some of their properties. Also we characterized the intuitionistic fuzzy generalized semi-pre super connected space. 2010 AMS Classification: 54A...

The fuzzy rough sets and generalized fuzzy rough sets have been extended by three pairs of fuzzy logical operators to deal with real-valued data for a variety of models. Three pairs of fuzzy logical operators are triangular norm or t-norm and its dual (t-conorm), residual implicator or R-implicator and its dual, fuzzy implicator and t-norm, which are frequently discussed in generalization model...