In the cases of control systems where physical mechanisms are not well known due to high complexity and nonlinearity, a fuzzy relational model may be useful. In this paper, we propose a recursive parameter tuning algorithm for the identification of fuzzy relational model for an unknown dynamic system. Furthermore, using the fact that a dynamic system is represented by the relational strength be...

Quantitative and qualitative fuzzy measures have been proposed to hesitant fuzzy sets 9 (HFSs) from different points. However, few of the existing HFSs fuzzy measures refer to the grey 10 relational analysis (GRA) theory. Actually, the GRA theory is very useful in the fuzzy measure 11 domain, which has been developed for such the intuitionistic fuzzy sets. Therefore, in this paper, 12 we apply ...

Medoids-based fuzzy relational clustering generates clusters of objects based on relational data, which records pairwise similarity or dissimilarities among objects. Compared with single-medoid based approaches, multiple-weighted medoids has shown superior performance in clustering. In this paper, we present a new version of fuzzy relational clustering in this family called fuzzy clustering wit...

This paper comprises two parts, the first deals with the conception of a class of Hybrid Granular Min-Max Fuzzy-Neuro Relational Learners, for which a learning scheme was devised that uses an exhaustive search over the fuzzy partitions of involved variables, automatic fuzzy hypotheses generation, formulation and testing, and successive approximation procedure of Min-Max relational equations. Th...

Fuzzy relational identi"cation builds a relational model describing a system's behaviour by a nonlinear mapping between its variables. In this paper, we propose a new fuzzy relational algorithm based on the simpli"ed max}min relational equation. The algorithm presents an adaptation method applied to the gravity-centre of each fuzzy set based on the error integral value between the measured and ...

Fuzzy relational identification builds a relational model describing system’s behaviour by a nonlinear mapping between its variables. In this paper, we propose a new fuzzy relational algorithm based on simplified max-min relational equation. The algorithm presents an adaptation method applied to gravity-center of each fuzzy set based on error integral value between measured and predicted system...

The aim of this thesis is to extend the fuzzy relational product calculations from binary to ternary relations, and apply the ternary fuzzy relational product calculations to processing of the URBS data. It is demonstrated that, by ternary fuzzy relational product calculations, the respondents with the similar cognitive structures can be clustered into groups and cognitive structures of those g...

Fuzziness in databases is used to denote uncertain or incomplete data. Relational Databases stress on the nature of the data to be certain. This certainty based data is used as the basis of the normalization approach designed for traditional relational databases. But real world data may not always be certain, thereby making it necessary to design an approach for normalization that deals with fu...

With respect to multiple attribute decision making (MADM) problems in which the attribute values take the form of hesitant fuzzy elements, the traditional grey relational projection (GRP) method is extended to solve multiple attribute decision making problems under hesitant fuzzy environment. Based on the hesitant fuzzy decision matrix provided by decision makers, all feasible alternatives are ...