The fuzzy sets defining the linguistic variable values can be seen as a fuzzy partition of the linguistic variable. The membership functions obtained using fuzzy clustering algorithms are defined with respect to the group prototypes, and they cannot be used to define the linguistic variable values. We introduce several criteria to pass from the clustering membership functions to the linguistic ...

In this study an academician selection system has been developed for universities using fuzzy weighting and fuzzy ranking. In the system, effects of many criteria and views of many experts are evaluated for selection. Number of criteria, number of linguistic variables of criteria, names of linguistic variables, membership functions of linguistic variables, number of experts and alternatives can...

The present article proposes a fuzzy set-based classifier with a better learning and generalization capability. The proposed classifier exploits the feature-wise degree of belonging of a pattern to all classes, generalization in the fuzzification process and the combined class-wise contribution of features effectively. The classifier uses a -type membership function and product aggregation reas...

In this paper, we propose a new machine learning approach based on AFS (Axiomatic Fuzzy Sets) fuzzy logic, in attempt to provide a better model with interpretability. First, we will concisely present the AFS theory. Second, we will propose new membership functions for fuzzy sets and their logic operations. Third, we will design a new machine learning algorithm based on the new membership functi...

In this work, we extend the genetic lateral tuning of membership functions [1] based on the linguistic 2-tuples representation [2], in order to also perform a tuning of the support amplitude of the membership functions. To do so, we present a new symbolic representation which extends the linguistic 2-tuples representation model with a parameter β to represent the amplitude variation of the supp...

The present study considers a fuzzy color system in which three membership functions are constructed on the RGB color triangle. This system can process a fuzzy input (as the membership values of subjects) to an RGB system and output the center of gravity of three weights associated with respective grades. Three membership functions are applied to the RGB color triangle relationship. By treating...

This paper introduces an advanced codebook model for foreground-background segmentation. The improvement is two-fold. First, to cope with changing global lumination, we develop the conventional codebook with confidence functions. Similarities of both brightness and normalized color-vector are integrated confidence-weightedly to form overall similarity. A designed codeword-update progress also c...

The commonly accepted theory of fuzzy numbers (Czogała and Pedrycz, 1985) is that set up by Dubois and Prade (1978), who proposed a restricted class of membership functions, called (L,R)–numbers with shape functions L and R. However, approximations of fuzzy functions and operations are needed if one wants to follow Zadeh’s (Zadeh 1975; 1983) extension principle. It leads to some drawbacks that ...

Fuzzy logic has been successfully applied in various fields, but these applications have usually suffered from the problem of low speed. Typically, calculation of the matching degree requires very high latency, which limits the overall inference speed. In this paper, we prove that the matching degree between two trapezoid-shaped membership functions can be obtained without traversing all the el...