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 ...

Fuzzy decision making is the collection of single or multicriteria techniques aiming at selecting the best alternative in case of imprecise, incomplete, and vague data. This chapter reviews the fuzzy decision making literature and summarizes the review results by tabular and graphical illustrations. The classification is based on the new extensions of fuzzy sets: Intuitionistic, hesitant, and t...

Selection of appropriate supplier(s) for success of an organization is particularly a valuable necessity, hence apart from the common criteria such as logistics, service and quality, this paper discusses most of the key decision variables which can play a critical role in case of the supplier selection. In this study, analytic network process (ANP) method is used because it considers the relati...

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...

Fuzzy predictive control integrates conventional model predictive control with techniques from fuzzy multicriteria decision making, translating the goals and the constraints to predictive control in a transparent way. The information regarding the (fuzzy) goals and the (fuzzy) constraints of the control problem is combined by using a decision function from the theory of fuzzy sets. This paper i...

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...

the success of artificial recharge schemes requires the identification of suitable site. the use of fuzzy set theory in site selection projects allows the decision-makers to incorporate unquantifiable information into decision model. in this paper, site selection of artificial groundwater recharges using an integrated method of fuzzy topsis and ahp has been done in raster environment of gis. th...