Certain scholars have generalized the theory of fuzzy set, but picture hesitant set (PHFS) has received massive attention from distinguished scholars. PHFS is combination (PFS) and (HFS) to cope with awkward complicated information in real-life issues. The well-known characteristic that sum maximum membership, abstinence, non-membership degree limited unit interval. This manuscript aims develop...

Fuzzy control can be interpreted as an approximation technique for a control function based on typical, imprecisely speciied input{output tuples that are represented by fuzzy sets. The imprecision is characterized by similarity relations that are induced by transformations of the canonical distance function between real numbers. Taking this interpretation of fuzzy controllers into account, in o...

The well-known fuzzy c-means algorithm is an objective function based fuzzy clustering technique that extends the classical k-means method to fuzzy partitions. By replacing the Euclidean distance in the objective function other cluster shapes than the simple (hyper-)spheres of the fuzzy c-means algorithm can be detected, for instance ellipsoids, lines or shells of circles and ellipses. We propo...

This paper presents a new method to design power system stabilizer (PSS) using fuzzy wavelet neural network (FWNN) for stability enhancement of a multi-machine power system. In the proposed approach, Wavelet Neural Network (WNN) is used to construct a well localized in both time and frequency domains consequent part for each fuzzy rule of a Takagi-Sugeno-Kang (TSK) fuzzy model. In designing the...

Similarity measures computed by kernels are well studied and a vast literature is available. In this work, we use distance-based kernels to define a new similarity measure for fuzzy sets. In this sense, a distance-based kernel on fuzzy sets implements a similarity measure for fuzzy sets with a geometric interpretation in functional spaces. When the kernel is positive definite, the similarity me...

Object recognition is a very important task in industrial applications. Attributed string matching is a well-known technique for pattern matching. The present paper proposes a fuzzy string-matching approach for two-dimensional object recognition. The fuzzy numbers are used to represent the edit costs. Therefore, the edit distances are also presented as fuzzy numbers. The attributed string-match...

EDF is a classic dynamic embedded realtime multi-task scheduling algorithm. In an embedded soft real-time system, the deadline missing ratio is an important metric to evaluate system performance. When an embedded soft realtime system is overloaded, EDF algorithm is not effective. Considering the unsteadiness and unpredictability of a practical task running environment due to the unsteadiness of...

A new method for solving intuitionistic fuzzy multi-attribute decision making problem is proposed, in which the information of attribute weights is incompletely known. Considering much information about hesitancy and vagueness inherited to intuitionistic fuzzy sets, a new class of distance for describing the deviation degrees between intuitionistic fuzzy sets is introduced. Furthermore, the mea...

Fuzzy C-Mean (FCM) is an unsupervised clustering algorithm based on fuzzy set theory that allows an element to belong to more than one cluster. Where fuzzy means “unclear” or “not defined” and c denotes “clustering”. In FCM the number of cluster are randomly selected. [15] FCM is the advanced version of K-means clustering algorithm and doing more work than K-means. K-Means just needs to do a di...

Recently, many scholars investigated interval, triangular, and trapezoidal approximations of fuzzy numbers. These researches can be grouped into two classes: the Euclidean distance class and the non-Euclidean distance class. Most approximations in the Euclidean distance class can be calculated by formulas, but calculating approximations in the other class is more complicated. In this paper, we ...