Fuzzy Inference System and Fuzzy Neural Inference System Applied to Risk Matrix Classification in Projects

Projects are essential for organizations to transform strategies into results, but uncertain events can impose risks achieve a certain objective. Risk management aims support an organization in deciding how deal with risks, prioritizing them through the application of Matrices (RMs). RMs or Probability and Impact is used decision-making, helping classify prioritize decide which will be ad-dressed, monitored, tolerated. supposedly easy build explain, according literature they may contain uncertainties. To uncertainty, it recommended apply Fuzzy Inference System, based on Set Theory (FST) Neural System presence artificial neural network. Thus, aim this paper was develop (FIS) (FNIS) classification MRs projects reduce uncertainty. The analysis results indicated that two systems resulted continuous rule by smoothing boundary areas between each RM classes, reducing uncertainty improving risk classification. Both showed good However, obtained FNIS were more consistent. main contribution work lies possibility decision making present RMs.