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...

In this paper, a new way of optimizing fuzzy logic is introduced. This way is used to optimize the output of Interval Type-2 Fuzzy Logic controller by replacing the Defuzzification stage by the Optimization algorithm. The algorithm chooses the best crisp output variable from the type-reduced set which is the output of the Type-Reduction stage instead of averaging the set extremes which was perf...

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...

This article describes an extension to previously developed constraint techniques. These enhanced constraint methods will enable the study of large computational chemistry problems that cannot be easily handled with current constrained molecular dynamics (MD) methods. These methods are based on an O( N solution to the constrained equations of motion. The benefits of this approach are that (1) t...

In this paper, analytical structures of TITO (two-input two-output) Mamdani fuzzy PI/PD controllers are investigated with respect to conventional PI/PD control and variable gain control. Components of the fuzzy controllers include two input fuzzy sets for each input variable, five singleton output fuzzy sets for each output variable, 16 fuzzy rules, product AND fuzzy logic operator, the Mamdani...

Facility location decision is basically viewed as a long-term strategy, so the inherited uncertainty of main parameters ought to be taken into account in order to make models applicable. In this paper, we examine the impact of uncertain transportation costs and customers' demands on the choice of optimal location decisions and allocation plans. This leads to the formulation of the facility loca...

Due to the contradiction between high precision control with complexity of fuzzy controller design, an method for multi-variable fuzzy controller design is presented. A dynamic compensation model for the fuzzy controller is introduced, which simplify the analysis and design of multi-variable fuzzy controller, and improve control performance. The method is applied to high precision water tank te...