Interval type-2 fuzzy set (IT2FS) offers interesting avenue to handle high order information and uncertainty in decision support system (DSS) when dealing with both extrinsic and intrinsic aspects of uncertainty. Recently, multiple attribute decision making (MADM) problems with interval type-2 fuzzy information have received increasing attentions both from researchers and practitioners. As a re...

We extend the shape signature based on the distance of the boundary points from the shape centroid, to the case of fuzzy sets. The analysis of the transition from crisp to fuzzy shape descriptor is first given in the continuous case. This is followed by a study of the specific issues induced by the discrete representation of the objects in a computer. We analyze two methods for calculating the ...

Type-2 (T2) fuzzy variable is an extension of an ordinary fuzzy variable. In fuzzy possibility theory, T2 fuzzy variable is defined as a measurable map from the universe to the set of real numbers, and the possibility of a T2 fuzzy variable takes on a real number is a regular fuzzy variable (RFV). T2 fuzziness, which is usually used to handle linguistic uncertainties, can be described as T2 fuz...

Rough set theory introduced by Pawlak [8] is based on equivalence relations. The definition of basic rough sets depends upon a single equivalence relation defined on the universe or several equivalence relations taken one each taken at a time. In the view of granular computing, classical rough set theory is based upon single granulation. The basic rough set model was extended to rough set model...

Abstract This paper has represented a soft-set in the type-2 environment by its simplest form as an augmentation to theories. Furthermore, we have applied fuzzy soft set(T2FSS) using our most straightforward representation find solution of decision-making-problem (DMP) based-on T2FSS well weighted set (WT2FSS). We proposed two definitions, namely, Mid- $$\alpha $$ <mml:math xmlns:mml="http://ww...

In interval type-2 fuzzy logic controllers (IT2-FLCs), the output processing includes type reduction and defuzzification. Recently, researchers have proposed many efficient type reduction algorithms, but there are no effective schemes to improve the output of defuzzification. This paper presents a geneticalgorithm-based type reduction algorithm, which reduces the type of an interval type-2 fuzz...

Similarity measure is a very important problem in fuzzy soft set theory. In this paper, seven similarity measures of fuzzy soft sets are introduced, which are based on the normalized Hamming distance, the normalized Euclidean distance, the generalized normalized distance, the Type-2 generalized normalized distance, the Type-2 normalized Euclidean distance, the Hausdorff distance and the Chebysh...

ress as: , Alexa and hosti 013.11.0 Abstract The interval type-2 fuzzy logic controller (IT2-FLC) is able to model and minimize the numerical and linguistic uncertainties associated with the inputs and outputs of a fuzzy logic system (FLS). This paper proposes an interval type-2 fuzzy PD (IT2F-PD) controller for nonlinear inverted pendulum. The proposed controller uses the Mamdani interval type...