Using artificial neural network to define fuzzy comparators in FSQL with the criterion of some decision-maker

Abstract

At present we have a FSQL server available for Oracle© Databases, programmed in PL/SQL. This server allows us to query a Fuzzy or Classical Database with the FSQL language (Fuzzy SQL). The FSQL language is an extension of the SQL language which permits us to write flexible (or fuzzy) conditions in our queries to a fuzzy or traditional database. In this paper we have incorporated a method of ranking fuzzy numbers using Neural Networks to compare fuzzy quantities in FSQL. The main advantage is that any user can to train his own fuzzy comparator for any specific problem We consider that this model satisfies the requirements of Data Mining systems (high-level language, efficiency, certainty, interactivity, etc) and this new level of personal configuration makes the system very useful and flexible. © Springer-Verlag Berlin Heidelberg 2001.