Belief rule-based dependence assessment method under interval uncertainty

Human reliability analysis (HRA) is of great significance for probabilistic risk assessment, and the technique for human error rate prediction (THERP) has been widely applied to assess the dependence among HRA. However, uncertainties in analyst's judgment and experts' knowledge, especially interval uncertainty in analyst's judgment, have been ignored by existing methods. To this end, the belief rule-based system is employed to model uncertainties in experts' knowledge in this paper, and the interval belief distribution is used to model interval uncertainty in analyst's judgment. Then, a new belief rule-based dependence assessment method is proposed, and two case studies are used to illustrate the effectiveness of the proposed method. Experimental results demonstrate that the proposed method could not only model uncertainty using belief rules and interval belief distributions, but also provide a novel and effective way for human reliability analysis.