This paper is concerned with the fuzzy support vector classification, in which both of the type of the output training point and the value of the final fuzzy classification function are triangle fuzzy number. First, the fuzzy classification problem is formulated as a fuzzy chance constrained programming. Then, we transform this programming into its equivalence quadratic programming. Final, a fu...

recently, tuning the weights of the rules in fuzzy rule-base classification systems is researched in order to improve the accuracy of classification. in this paper, a margin-based optimization model, inspired by support vector machine classifiers, is proposed to compute these fuzzy rule weights. this approach not only  considers both accuracy and generalization criteria in a single objective fu...

In this paper, a solution procedure for the solution of the system of fuzzy differential equations ẋ(t) = α(A− In) [t(A− In) + In]−1 x(t), x(0) = x0 where A is real n × n matrix which does not have eigenvalues on R− and x0 is a vector consisting of n fuzzy numbers is developed. In addition, the necessary and sufficient condition for the existence of fuzzy solution is presented. An example is pr...

The production of a process is expected to meet customer demands, specifications or engineering tolerances. The ability of a process to meet these expectations is expresed as a single number using a process capability index. When the quality of the products relates to more than one characteristic, multivariate process capability indices are applied. As it is known, in some circumstances we are ...

Support vector machines (SVMs) and fuzzy rule systems are functionally equivalent under some conditions. Therefore, the learning algorithms developed in the field of support vector machines can be used to adapt the parameters of fuzzy systems. Extracting fuzzy models from support vector machines has the inherent advantage that the model does not need to determine the number of rules in advance....

This paper presents a novel approach to estimate the pose position of the degraded face images using fuzzy vector representation. We focus on the development of fuzzy-manifold as an interpolation line between all the available learning data and the fuzzy distance calculation as the classifier. Crisp-based vector of the face image is firstly transformed into fuzzy-based vector, to deal with the ...

In this paper, we intend to offer a new method based on fuzzy neural networks for finding a real solution of fuzzy equations system. Our proposed fuzzified neural network is a fivelayer feed-back neural network that corresponding connection weights to output layer are fuzzy numbers. The proposed architecture of artificial neural network, can get a real input vector and calculates it’s correspon...

in 1997, fang proposed the concept of boundedness of $l$-fuzzy setsin $l$-topological vector spaces. since then, this concept has beenwidely accepted and adopted in the literature. in this paper,several characterizations of bounded $l$-fuzzy sets in$l$-topological vector spaces are obtained and some properties ofbounded $l$-fuzzy sets are investigated.

A new algorithm namely, fuzzy zero point method is proposed for finding a fuzzy optimal solution for a fuzzy transportation problem where the transportation cost, supply and demand are trapezoidal fuzzy numbers. The optimal solution for the fuzzy transportation problem by the fuzzy zero point method is a trapezoidal fuzzy number. The solution procedure is illustrated with numerical example. Mat...