Several authors have proposed different methods to find the solution of fully fuzzy linear programming (FFLP) problems. But all the existing methods are based on the assumption that all the fuzzy coefficients and the fuzzy variables are non-negative fuzzy numbers. in this paper a new method is proposed to solve an FFLP problems with arbitrary fuzzy coefficients and arbitrary fuzzy variables, th...

We discuss some optimization problems for fuzzy variable functions and show two interesting results. First result is related to conditions for existence of global optimal solutions for some general class of optimization problems on E, the space of compacts, upper semicontinuous and normal fuzzy sets of R. The second result is about preservation of local optimality points, via Zadeh’s principle ...

In this paper an adaptive neuro fuzzy inference system based on interval Gaussian type-2 fuzzy sets in the antecedent part and Gaussian type-1 fuzzy sets as coefficients of linear combination of input variables in the consequent part is presented. The capability of the proposed method (we named ANFIS2) to function approximation and dynamical system identification is shown. The ANFIS2 structure ...

Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic an...

For interval-valued fuzzy datasets, people have started to do research on interval-valued fuzzy rough sets and relevant models. However, these models could not be effectively applied to handle the real-valued datasets such as interval-valued fuzzy datasets as variable precision problems were not considered in interval-valued fuzzy rough sets. In this paper, fuzzy variable precision rough sets a...

The paper aims to expand the concept of linguistic variable. The study analyzes the common conclusion forms in the evaluation project. The evaluation often makes the final conclusion by analyzing the fuzzy number and its membership function. However, the information of modified word or phrase (“largely”, “preliminary” and “unclear”) has got lost in analysis. The research believe these modified ...

When we deal with the estimator of a parameter, it is important for us to find an estimator with minimum variance. For this reason, this paper discuss on the variance of fuzzy random variable. There are two different approaches to the definition of the variance of a fuzzy random variable. In the first one, the variance of the fuzzy random variable is defined as a crisp number by using defuzzifi...

Fuzziness plays an essential role in the real world. Fuzzy set theory has been developed very fast since it was introduced by Zadeh (1965) [1]. A fuzzy set was characterized with its membership function by Zadeh. The term fuzzy variable was fist introduced by Kaufmann (1975) [2], and then appeared in Zadeh (1978) [3] and Nahmias (1978) [4] as a fuzzy set of real numbers. In order to establish t...

In order to efficiently manage and use knowledge, ontology technologies are widely applied to various kinds of domain knowledge. This paper proposes a Chinese term clustering mechanism for generating semantic concepts of a news ontology. We utilize the parallel fuzzy inference mechanism to infer the conceptual resonance strength of a Chinese term pair. There are four input fuzzy variables, cons...

Scalarization of the multiobjective programming problems with fuzzy coefficients using the embedding theorem and the concept of convex cone (ordering cone) is proposed in this paper. Since the set of all fuzzy numbers can be embedded into a normed space, this motivation naturally inspires us to invoke the scalarization techniques in vector optimization problems to evaluate the multiobjective pr...