Type-2 fuzzy sets and complex fuzzy sets are both three dimensional extensions of type-1 fuzzy sets. Complex fuzzy sets come in two forms, the standard form, postulated in 2002 by Ramot et al., and the 2011 innovation of pure complex fuzzy sets, proposed by Tamir et al.. In this paper we compare and contrast both forms of complex fuzzy set with type-2 fuzzy sets, as regards their rationales, ap...

This paper focusses on the application of fuzzy control techniques (fuzzy type-1 and type-2) and their hybrid forms (Hybrid adaptive fuzzy controller and fuzzy-PID controller) in the area of stabilized platforms. It represents an attempt to cover the basic principles and concepts of fuzzy control in stabilization and position control, with an outline of a number of recent applications used in a...

In this paper, we incorporate the concept of fuzzy set theory into the support vector regression (SVR). In our proposed method, target outputs of training samples are considered to be fuzzy numbers and then, membership function of actual output (objective hyperplane in high dimensional feature space) is obtained. Two main properties of our proposed method are: (1) membership function of actual ...

In this paper, we present a general framework for the study of interval type-2 rough fuzzy sets by using both constructive and axiomatic approaches. First, several concepts and properties of interval type-2 fuzzy sets are introduced. Then, a pair of lower and upper interval type-2 rough fuzzy approximation operators with respect to a crisp binary relation is proposed. Classical representations ...

Type – II fuzzy number is introduced in decision making analysis as a concept that is capable to effectively deal with uncertainty in the information about a decision. As type – II fuzzy number is represented by possibility distribution, it is hard to determine which type – II fuzzy number is greater than the other. In this paper, a new methodology for ranking type – II fuzzy number is proposed...

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Many problems arise in practical applications when data is extracted from a group of experts, all of whom do not collectively agree. The theory of Type 2 Fuzzy Multisets is capable of modelling these types of uncertainties in decision making. The purpose of this paper is to introduce the study of various algebraic structures of Type 2 Fuzzy Multisets. As a beginning of this study, the concept o...

fuzzy groups and fuzzy theory have a lot of applications in several sciences such as mathematics, computer science, computer and electrical engineering. hence, counting the number of fuzzy subgroups of finite groups to classify them is an important issue in fuzzy theory. the main goal of this paper is to give an explicit formula for the number of fuzzy subgroups of a finite cyclic group g z p1 ...