Type-II fuzzy sets are used to convey the uncertainties in the membership function of type-I fuzzy sets. Linguistic information in expert rules does not give any information about the geometry of the membership functions. These membership functions are mostly constructed through numerical data or range of classes. But there exists an uncertainty about the shape of the membership, that is, wheth...

This paper presents a literature review of applications using type-2 fuzzy systems in the area of image processing. Over the last years, there has been a significant increase in research on higher-order forms of fuzzy logic; in particular, the use of interval type-2 fuzzy sets and general type-2 fuzzy sets. The idea of making use of higher orders, or types, of fuzzy logic is to capture and repr...

envelopment analysis (dea) is a very eective method to evaluate the relative eciency of decision-making units (dmus). dea models divided all dmus in two categories: ecient and inecientdmus, and don't able to discriminant between ecient dmus. on the other hand, the observedvalues of the input and output data in real-life problems are sometimes imprecise or vague, suchas interval data, ...

In recent years, the type-2 fuzzy sets theory has been used to model and minimize the effects of uncertainties in rule-base fuzzy logic system (FLS). In order to make the type-2 FLS reasonable and reliable, a new simple and novel statistical method to decide interval-valued fuzzy membership functions and probability type reduce reasoning method for the interval-valued FLS are developed. We have...

In this article, we propose a method to deal with incomplete interval-valuedhesitant fuzzy preference relations. For this purpose, an additivetransitivity inspired technique for interval-valued hesitant fuzzypreference relations is formulated which assists in estimating missingpreferences. First of all, we introduce a condition for decision makersproviding incomplete information. Decision maker...

Interval type-2 fuzzy logic system; Interval type-2 fuzzy PID controller; Inverted pendulum system; Hardware-in-the-loop (HIL) simulation Abstract In this study, we propose an embedded real-time interval type-2 fuzzy proportional – integral – derivative (IT2F-PID) controller which is a parallel combination of the interval type-2 fuzzy proportional – integral (IT2F-PI) controller and the interva...

This paper proposes a least squares method and a goal programming method to get the priority of the intuitionistic fuzzy preference relation (IFPR). The relation between the IFPR and the interval fuzzy number preference relation (IFNPR) is established by splitting the IFPR into the membership degree interval judgment matrix and the non-membership degree interval judgment matrix. Considering the...

A novel learning methodology based on a hybrid mechanism for training interval singleton type-2 Takagi-SugenoKang fuzzy logic systems uses recursive orthogonal least-squares to tune the type-1 consequent parameters and the steepest descent method to tune the interval type-2 antecedent parameters. The proposed hybrid-learning algorithm changes the interval type-2 model parameters adaptively to m...