An Uzawa method is presented for solving fuzzy linear systems whose coefficient matrix is crisp and the right-hand side column is arbitrary fuzzy number vector. The explicit iterative scheme is given. The convergence is analyzed with convergence theorems and the optimal parameter is obtained. Numerical examples are given to illustrate the procedure and show the effectiveness and efficiency of t...

In the current paper, consider the fuzzy normed linear space $(X,N)$ which is defined by Bag and Samanta. First, we construct a new fuzzy topology on this space and show that these spaces are Hausdorff locally convex fuzzy topological vector space. Some necessary and sufficient conditions are established to illustrate that the presented fuzzy topology is equivalent to two previously studied fuz...

In this paper we propose a fuzzy goal programming method for obtaining a satisfactory solution to a bi-level multi-objective absolutevalue fractional programming (BLMO-A-FP) problems. In the proposed approach, the membership functions for the defined fuzzy goals of all objective functions at the two levels as well as the membership functions for vector of fuzzy goals of the decision variables c...

In order to combine a fast multiclass classification method with an effective binary classification method, we have developed a prototype learning/matching scheme that can be integrated with support vector machines (SVM) for vector-matching applications. This prototype classification method employs a learning process to determine both the number and the location of prototypes. The learning proc...

In this paper, the fuzzy nonlinear programming problem is discussed. In order to obtain more accurate solution, the properties of fuzzy set and fuzzy number with linear membership function and fuzzy maximum decision maker is utilized to fuzzifying the crisp problem . An example is provided to show the effectiveness of the proposed method.

We introduce a fuzzy rough granular neural network (FRGNN) model based on the multilayer perceptron using a back-propagation algorithm for the fuzzy classification of patterns. We provide the development strategy of the network mainly based upon the input vector, initial connection weights determined by fuzzy rough set theoretic concepts, and the target vector. While the input vector is describ...

in the mathematical analysis, there are some theorems and definitions that established for both real and fuzzy numbers. in this study, we try to prove  bernoulli's inequality in fuzzy real numbers with some of its applications. also, we prove two other theorems in fuzzy real numbers which are proved before, for real numbers.

in this paper, a new method is proposed to find the fuzzy optimal solution of fully fuzzy linear bilevel programming (fflblp) problems by representing all the parameters as triangular fuzzy numbers. in the proposed method, the given fflblp problem is decomposed into three crisp linear programming (clp) problems with bounded variables constraints, the three clp problems are solved separately and...

fuzzy measures are suitable in analyzing human subjective evaluation processes. several different strategies have been proposed for distance of fuzzy numbers. the distances introduced for fuzzy numbers can be categorized in two groups:1. the crisp distances which explain crisp values for the distance between two fuzzy numbers.2. the fuzzy distance which introduce a fuzzy distance for normal fuz...

We offer an efficient method to reduce the number of support vectors for Fuzzy Support Vector Machine. Firstly, we consider the Fuzzy Support Vector Machine model which was proposed by Lin and Wang. For the reducing the number of support vectors, we apply the l0 regularization term to the dual form of this model. The resulting optimization problem is non-smooth and non-convex. The l0 is then re...