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...

The article presents a multidimensional type 2 epistemic fuzzy arithmetic (MT2EF-arithmetic) based on the new body definition of set (T2FS), which in authors’ opinion, is more suitable for computing than current versions (FA) border T2FS. proposed MT2EF-arithmetic designed variables and has mathematical properties that allow obtaining universal algebraic calculation results. performs calculatio...

As a result of emerging computation technologies, information systems are developed to support various processes of enterprises. ERP (Enterprise Resource Planning) has been a leading EIS (Enterprise Information Systems) application and companies are allocating resources to such new projects. However, studies report that most of the projects fail or cannot reach the desired outcomes selecting in...

Words mean different things to different people, and so are uncertain. We, therefore, need a fuzzy set model for a word that has the potential to capture their uncertainties. In this paper I propose that an interval type-2 fuzzy set (IT2 FS) be used as a FS model of a word, because it is characterized by its footprint of uncertainty (FOU), and therefore has the potential to capture word uncerta...

In this work, we introduce the concept of fuzzy parameterized intervalvalued fuzzy soft set theory (fpivfss) and study their operations. We then define fpivfss-aggregation operator to form fpivfss-decision making method that allows constructing more efficient decision processes. Finally, some numerical examples are employed to substantiate the conceptual arguments.

This paper presents a new clustering algorithm named improved type-2 possibilistic fuzzy c-means (IT2PFCM) for fuzzy segmentation of magnetic resonance imaging, which combines the advantages of type 2 fuzzy set, the fuzzy c-means (FCM) and Possibilistic fuzzy c-means clustering (PFCM). First of all, the type 2 fuzzy is used to fuse the membership function of the two segmentation algorithms (FCM...

controller design remains an elusive and challenging problem foruncertain nonlinear dynamics. interval type-2 fuzzy logic systems (it2fls) incomparison with type-1 fuzzy logic systems claim to effectively handle systemuncertainties especially in the presence of disturbances and noises, but lack aformal mechanism to guarantee performance. in contrast, adaptive sliding modecontrol (asmc) provides...

Interval-valued fuzzy sets are based on the algebra of subintervals of the unit interval [0, 1]. We study valuations as a special type of measures on this algebra. We present a description of all valuations which preserve the standard fuzzy negation and extend the identity on the elements of the form (x, x). Consequences for sublattices are formulated. Keywords— Girard algebra, interval-valued ...