Fuzzy probability calculation with confidence intervals in Bayesian networks

In this study, we propose to use Buckley's confidence interval approach which has not been used before in the literature to calculate marginal and conditional fuzzy probabilities in Bayesian networks. We apply this approach to a real life problem and show that Buckley's confidence interval approach provides to indicate uncertainty better and represents knowledge more explicitly than determining fuzzy probabilities based only on the expert opinion in Bayesian networks.