A Methodology for Building Fuzzy Rule-Based Systems Integrating Expert and Data Knowledge

Historically, since Mamdani proposed his model of fuzzy rule-based system, a lot has changed in the construction process of this type of models. For a long time, the research efforts were directed towards the automatic construction of accurate models starting from data, making fuzzy systems almost mere function approximators. Realizing that this approach escapes from the original concept of fuzzy theory, more recently, researchers attention - focused on the automatic construction of more interpretable models. However, such models, although interpretable, can still not make sense to the expert. This paper proposes an interactive methodology for constructing fuzzy rule-based systems, which aims to integrate the knowledge extracted from experts and induced from data, hoping to contribute to the solution of the mentioned problem.