APPLICATION OF FUZZY LOGIC IN RELATIONAL DATABASES

Abstract

A fuzzy relational database model (FRDBM) is an extension of classical relational databases and this is related primarily to the possibility and ability to manipulate with imprecise and uncertain information. Consequently, classical relational databases incorporate elements of Zadeh’s fuzzy logic and fuzzy sets. The issue of data uncertainty and their representation has been represented as very important topic in many areas and applications such as geographic information systems (GIS) and spatial data representations, Data Mining systems, statistical databases, fuzzy information retrieval etc. Fuzzy approach is continually studying and constantly appearing new possibilities for application of this concept in the different problem analysis. Firstly, database managers analyze the possibility of fuzzy queries generating and adding of imprecise information in fuzzy relational database models. In this sense, various fuzzy database models have been proposed. The next step is analysis, characterization and generalization of data such as functional dependency, data redundancy, data anomalies etc. This paper reviews the most significant research in the areas of fuzzy database modeling.