Decision makers sometimes tend to express their preferences in intuitionistic fuzzy form. Based on evidence theory and grey relational analysis (GRA) technique, this paper aims at investigating multiple attribute decision making problems, in which both attribute values and weight values take the form of intuitionistic fuzzy numbers (IFNs). To this end, each intuitionistic fuzzy evaluation ratin...

Medoid-based fuzzy clustering generates clusters of objects based on relational data, which records pairwise similarities or dissimilarities among objects. Compared with single-medoid based approaches, our recently proposed fuzzy clustering with multipleweighted medoids has shown superior performance in clustering via experimental study. In this paper, we present a new version of fuzzy relation...

Many data sets to be clustered are stored in relational databases. Having a clusterization algorithm implemented in SQL provides easier clusterization inside a relational DBMS than outside with some alternative tools. In this paper we propose Fuzzy c-Means clustering algorithm adapted for PostgreSQL open-source relational DBMS.

The aim of this thesis is to develop the fuzzy relational calculus. To develop this calculus, we study four algebraic formalisations of fuzzy relations which are called fuzzy relation algebras, Zadeh categories, relation algebras and Dedekind categories, and we strive to arrive at their representation theorems. The calculus of relations has been investigated since the middle of the nineteenth c...

Fuzzy Databases have been a fertile research area that has produced a wide variety of remarkable solutions for the storage and manipulation of imperfect information. Proposals can be found in the three most relevant data models: relational, object-oriented, and object-relational. Query capabilities have been especially studied in the context of the relational data model, while in object models ...

Successes with kernel-based classification methods have spawned many recent efforts to kernelize clustering algorithms for object data. We extend this idea to the relational data case by proposing kernelized forms of the non-Euclidean relational fuzzy (NERF) and hard (NERH) c-means algorithms. We show that these relational forms are dual to kernelized forms of fuzzy and hard c-means (FCM, HCM) ...

In this paper it has been studied the sequence of membership functions and of join spaces (see [7]), determined by a class of 1–hypergroups which are not complete (see [2]).

We provide a self contained survey of the state of art of the fuzzy binary relations and some of their applications.