Type-2 fuzzy sets, which are characterized by membership functions (MFs) that are themselves fuzzy, have been attracting interest. This paper focuses on advancing the understanding of interval type-2 fuzzy logic controllers (FLCs). First, a type-2 FLC is evolved using Genetic Algorithms (GAs). The type-2 FLC is then compared with another three GA evolved type-1 FLCs that have different design p...

This paper reports the use of simulated annealing to design more efficient fuzzy logic systems to model problems with associated uncertainties. Simulated annealing is used within this work as a method for learning the best configurations of interval and general type-2 fuzzy logic systems to maximize their modeling ability. The combination of simulated annealing with these models is presented in...

We describe fuzzy sets of type-2 and look at the definition of some of the available operations. With the aid of the extension principle we suggest some operations for implementing the concept of containment between fuzzy sets of type-2. We discuss the idea of specificity of a fuzzy set. We suggest a procedure for calculating the specificity of a interval value type-2 fuzzy subset. We show the ...

Fuzzy Technique for Order Preference by Similarly to Ideal Solution (TOPSIS) is one of the most commonly used approaches in solving numerous multiple criteria decision making problems. It has been widely used in ranking of multiple alternatives with respect to multiple criteria with the superiority of fuzzy set type-1 and subjective weights. Recently, fuzzy TOPSIS has been merged with interval ...

The type-2 fuzzy sets was introduced by L. Zadeh as an extension of ordinary fuzzy sets. So the concept of type-2 fuzzy sets is also extended from type-1 fuzzy sets. If A is a type-1 fuzzy set and membership grade of x ∈ X in A is μA(x), which is a crisp number in [0, 1]. A type-2 fuzzy set in X is Ã, and the membership grade of x ∈ X in à is μÃ(x), which is a type-1 fuzzy set in [0, 1]. The el...

Hori (né Uemura) et al. formulated the fuzzy-Bayes decision rule extension of the Wald decision function to fuzzy ORand AND-connectives with multiple subjective distributions. This decision rule maps and transforms a state of nature to fuzzy events. In this context, the map of subjective distributions is called the subjective possibility distribution and the map of utility functions is called t...

A review of the applications of interval type-2 fuzzy logic in intelligent control has been considered in this paper. The fundamental focus of the paper is based on the basic reasons for using type-2 fuzzy controllers for different areas of application. Recently, bio-inspired methods have emerged as powerful optimization algorithms for solving complex problems. In the case of designing type-2 f...

A review of the optimization methods used in the design of type-2 fuzzy systems, which are relatively novel models of imprecision, is presented in this paper. The main aim of the work is to study the basic reasons for optimizing type-2 fuzzy systems for solving problems different areas of application. Recently, nature-inspired methods have emerged as powerful optimization algorithms for solving...

A method for response integration in modular neural networks with type-2 fuzzy logic for biometric systems p. 5 Evolving type-2 fuzzy logic controllers for autonomous mobile robots p. 16 Adaptive type-2 fuzzy logic for intelligent home environment p. 26 Interval type-1 non-singleton type-2 TSK fuzzy logic systems using the hybrid training method RLS-BP p. 36 An efficient computational method to...