This paper concerns the modeling of imprecision, vagueness, and uncertainty in databases through an extension of the relational model of data: the fuzzy rough relational database, an approach which uses both fuzzy set and rough set theories for knowledge representation of imprecise data in a relational database model. The fuzzy rough relational database is formally defined, along with a fuzzy r...

Ontology is an important part of the W3C standards for the Semantic Web used to specify standard conceptual vocabularies to exchange data among systems, provide reusable knowledge bases, and facilitate interoperability across multiple heterogeneous systems and databases. However, current ontology is not sufficient for handling vague information that is commonly found in many application domains...

in this paper, two sets of sufficient conditions are obtained to ensure the existence and stability of a unique equilibrium point of unforced first-order fuzzy relational dynamical systems by using two different approaches which are both based on the fuzzy relational matrix of the model.in the first approach, the equilibrium point of the system is one of the centers of the related membership fu...

This paper describes an extended relational database model based on probability theory and possibility theory. Fuzzy information and probabilistic information are incorporated into the relational databases simultaneously to represent fuzzy probability of events in the real-world applications. The tuples in such a relation are associated with a possibility distribution, and their attribute value...

The pioneer work of image compression/reconstruction based on fuzzy relational equations (ICF) and the related works are introduced. The ICF regards an original image as a fuzzy relation by embedding the brightness level into [0,1]. The compression/reconstruction of ICF correspond to the composition/solving inverse problem formulated on fuzzy relational equations. Optimizations of ICF can be co...

Fuzzy set theory has been extensively applied to extend various data models and resulted in numerous contributions, mainly with respect to the popular relational model or to some related form of it. To satisfy the need of modeling complex objects with imprecision and uncertainty, recently many researches have been concentrated on fuzzy semantic (conceptual) and object-oriented data models. This...

A new systematic algorithm to build adaptive linguistic fuzzy models directly from input-output data is presented in this paper. Based on clustering and projection in the input and output spaces, significant inputs are selected, the number of clusters is determined, rules are generated automatically, and a linguistic fuzzy model is constructed. Then, using a simplified fuzzy reasoning mechanism...

The object-relational database management systems (ORDBMS) appear due to the common acceptance of the object oriented paradigm and its integration with relational databases, combining the powerful modelling capabilities of the object oriented model and the robustness of relational model. ORDBMSs user defined types allow to create a framework for fuzzy information handling. This paper proposes t...

This paper proposes a logical reconstruction of the classical fuzzy relational database model to accommodate fuzzy disjunctive information. In query processing, we use two supplementary measurements, matching information and extra information, to model the concepts of imprecision and uncertainty, respectively. We also use these two supplementary measurements to determine the quality of answers ...