Approaches to mining association rules for genetic fuzzy systems

Abstract

Approaches to mining association rules for genetic fuzzy systems

Koburneeva M.P., Klimanskaja E.V.

Incoming article date: 11.12.2017

There are considered approaches to mining association rules of hybrid intelligence systems. A well-known algorithm for mining association rules is the Apriori algorithm, it can be used to process large items of quantitative values. The article presents modern methods of fuzzy data mining: with predefined membership functions, Aprior-based algorithms provide an easy way to analyze and describe the fuzzy association rules. FP-tree-based algorithms are particularly suitable to work with big data. Some types of fuzzy genetic algorithms are considered in detail, allowing to find both membership functions and fuzzy association rules.

Keywords: genetic fuzzy systems, hybrid intelligent systems, assosiation rules, data mining, genetic fuzzy data mining