Integration of data selection and classification by fuzzy logic

Highlights? We examine flexible data querying of relational databases by fuzzy logic. ? We also examine fuzzy data classification by fuzzy queries. ? It leads to integration of both processes into one entity. ? Access to relational database and database scheme do not have to be modified. A concept of integration of fuzzy data selection and classification by fuzzy Generalized Logical Condition (GLC) is presented in this paper. The GLC that extends SQL queries with fuzzy logic was developed for the purpose of fuzzy data selection. In order to classify data by generating fuzzy queries from fuzzy rules, the extension of the GLC was created. The proposed methodology leads to the integration of data selection and data classification into one entity, while the access to relational databases remains unchanged. The obtained approach was presented on data from the municipal and urban statistical database. Data selection and classification problems can often be described more naturally in terms of natural language rather than by crisp numbers.