A subjective methodology for risk quantification based on generalized fuzzy numbers
Uncertain information and domain experts' knowledge are inevitable in risk analysis of complex systems. Fuzzy reasoning is one of the ways to handle uncertainty. In addition, in order to represent the confidence degree of experts' subjective assessment, generalized fuzzy numbers are used for risk quantification in this paper. Based on the generalized fuzzy numbers arithmetic operation, a simple algorithm is developed to obtain final risk, which is also represented as generalized fuzzy number. A new similarity measure is proposed to determine the risk level. Compared with the previous works, our method is more reasonable. A numerical example is used to show the efficiency of the proposed method.
generalized fuzzy numbers risk analysis subjective assessment natural language