01715nam a2200265 a 450000100080000000500110000800800410001902400320006010000190009224501180011126001330022930000160036250000170037852008420039565000190123765000160125665000140127265300240128665300290131065300180133965300170135765300160137465300370139070000220142720286582020-01-08       2014    bl uuuu     u00u1 u    #d7 a10.1109/BRACIS.2014.612DOI1 aLIMA, H. P. de  aA methodology for building fuzzy rule-based systems integrating expert and data knowledge.h[electronic resource]  aIn: BRAZILIAN CONFERENCE ON INTELLIGENT SYSTEMS, 2014, São Carlos. Proceedings... [S. l.]: Conference Publishing Servicesc2014  ap. 300-305.  aBRACIS 2014.  aHistorically, 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.  aExpert opinion  aFuzzy logic  aKnowledge  aAlgoritmo genético  aConstruction methodology  aDomain expert  aFuzzy system  aMetodologia  aMultiobjective genetic algorithm1 aCAMARGO, H. de A.