Abstract:

In the course of reliability analysis on multi-state systems by using Bayesian networks, it is difficult to obtain the precision probability of different states of root nodes. So a method combining fuzzy theory with Bayesian networks is proposed. The linguistic variables from different experts, which denote the probability of different states of root nodes, are translated into triangular fuzzy-numbers. By steps viz. equalization, defuzzification and normalization, the precision probabilities are got. Inputting them into multistate Bayesian networks, the probabilities of leaf nodes in different states are calculated. And then, the posterior probability and risk achievement worth (RAW) importance of root node are got. The feasibility of this method is validated by an example. The application of this method can improve the ability of Bayesian networks to deal with uncertainty issues and make it play a greater role in improving the reliability and security of the multi-state uncertainty system.