Presenting a method to manage uncertainty in the form of a set of data rules using genetic algorithm

According to the rule-based knowledge display structure, extracting hidden patterns in the form of a set of rules is of great importance in intelligent decision-making systems. This paper presents an automated method for extracting rules directly from datasets. In the proposed method, the possibility and ability to manage the uncertainty of the theory of fuzzy sets is used in the modeling of rules. In order to reach the set of optimal fuzzy rules, the genetic algorithm is used, and in addition to reducing the repetitive rules, improving the fuzzy rules is done on them.