ranking fuzzy numbers plays a very important role in linguistic decision making and other fuzzy application systems. in spite of many ranking methods, no one can rank fuzzy numbers with human intuition consistently in all cases. shortcoming are found in some of the convenient methods for ranking triangular fuzzy numbers such as the coefficient of variation (cv index), distance between fuzzy set...

Ranking fuzzy numbers plays a very important role in linguistic decision making and other fuzzy application systems. In spite of many ranking methods, no one can rank fuzzy numbers with human intuition consistently in all cases. Shortcoming are found in some of the convenient methods for ranking triangular fuzzy numbers such as the coefficient of variation (CV index), distance between fuzzy set...

Ranking of fuzzy numbers plays a very important role in linguistic decision making and some other fuzzy application systems. Several strategies have been proposed for ranking of fuzzy numbers. Each of these techniques has been shown to produce nonintuitive results in certain cases. In this paper, some new approaches for ranking of trapezoidal fuzzy numbers are introduced. Keywords— Magnitude of...

This paper conducts a comparison analysis of some of the most common defuzzification techniques which helps rank fuzzy weights calculated from fuzzy comparison matrices through Fuzzy Analytic Hierarchy Process. Ranking of weights calculated through FAHP algorithms is of critical importance as it directly effects the decision making process. More so ranking of fuzzy numbers is also important in ...

This paper presents a modified feature ranking method on interclass separability based for fuzzy control application. Existing feature selection/ranking techniques are mostly suitable for classification problems. These techniques result in a ranking of the input feature or variables. Our modification exploits an arbitrary fuzzy clustering of the control output data. Using these output clusters ...

This paper presents a feature ranking method adapted to fuzzy modelling with output from a continuous range. Existing feature selection/ranking techniques are mostly suitable for classification problems, where the range of the output is discrete. These techniques result in a ranking of the input feature (variables). Our approach exploits an arbitrary fuzzy clustering of the model output data. U...

This paper presents a feature ranking method adapted to fuzzy modelling with output from a continuous range. Existing feature selection/ranking techniques are mostly suitable for classification problems, where the range of the output is discrete. These techniques result in a ranking of the input feature (variables). Our approach exploits an arbitrary fuzzy clustering of the model output data. U...

This study is devoted to address the notion of duality in Fully Intuitionistic Fuzzy Linear Programming Problems (FIFLP). The problem is addressed by using a revised simplex method with the Gaussian elimination process in fully intuitionistic fuzzy environment. Intuitionistic Fuzzy Trapezoidal Numbers (IFTrpN), along with the basic arithmetic techniques defined on them help in solving the (FIFL...

In this study the author discusses the problem of defuzzification by minimizing the weighted distance between two fuzzy quantities. Also, this study obtains the nearest point with respect to a fuzzy number and shows that this point is unique relative to the weighted distance. By utilizing this point, a method is presented for effectively ranking fuzzy numbers and their images to overcome the de...

one of the most effective tools for decline cost and time, quality improvement and consequently project performance enhancement especially in construction projects, is value engineering. there are linguistic judgments in many cases of value engineering studies in construction projects such as interior design, mechanical installations design, and etc. therefore multiple attribute decision-making...