Representation and manipulation of the vague concepts of partially true knowledge in the development of machine intelligence is a wide and challenging field of study. How to extract of approximate facts from vague and partially true statements has drawn significant attention from researchers in the fuzzy information processing. Furthermore, handling uncertainty from this incomplete information ...

In recent years, there have been a growing interest in developing Multi-Criteria Decision Making (MCDM) and Group Decision Making (GDM) using type-2 fuzzy sets and Intuitionistic Fuzzy Sets (IFSs) which provide frameworks to handle the encountered uncertainties in decision making models. Previous research has shown the power of type-2 fuzzy logic systems to handle the linguistic uncertainties. ...

Welcome to the Journal of Intelligent and Fuzzy Systems’s special issue for “FUZZYSS’2009: 1st International Fuzzy Systems Symposium”. Since its introduction by Prof. Lotfi A. Zadeh fuzzy logic has found numerous applications in many diverse areas. Scientific research related to fuzzy logic and its extensions is still an open and promising active research area. There is still a very long way to...

This paper proposes a fuzzy classifier based on type-2 fuzzy sets to be applied in land cover classification. The classifier is built on the basis of the available data and considers the merging of information drawn from different experts. The data regard a thematic mapper representing the land cover of a real plain cultivated area. The experts are represented by different bands which classify ...

in this study, we offer a general view at the area of fuzzy modeling and fuzzymodels, identify the visible development phases and elaborate on a new and promisingdirections of system modeling by introducing a concept of granular models. granularmodels, especially granular fuzzy models constitute an important generalization of existingfuzzy models and, in contrast to the existing models, generat...

As Granular Computing has gained interest, more research has lead into using different representations for Information Granules, i.e., rough sets, intervals, quotient space, fuzzy sets; where each representation offers different approaches to information granulation. These different representations have given more flexibility to what information granulation can achieve. In this overview paper, ...

Fuzziness (entropy) is a commonly used measure of uncertainty for type-1 fuzzy sets. For interval type-2 fuzzy sets (IT2 FSs), centroid, cardinality, fuzziness, variance and skewness are all measures of uncertainties. The centroid of an IT2 FS has been defined by Karnik and Mendel. In this paper, the other four concepts are defined. All definitions use a Representation Theorem for IT2 FSs. Form...

This paper presents a series of geometric definitions and algorithms that together form a type-2 geometric fuzzy inference system which can operate over a truly continuous domain, with no need for discretisation at any stage.

In this work we introduce the concept of a fusion operator for type-2 fuzzy sets as a mapping that takes m functions from [0, 1] to [0, 1] and brings back a new function of the same type. We study in depth the properties of pointwise fusion operators and representable fusion operators. Finally, we study the union and intersection of type2 fuzzy sets and we analyze when these functions are point...