Availability Assessment of Complex Systems under Parameter Uncertainty using Dynamic Evidential Networks

摘要

In many dynamic complex systems, the insufficiency of data makes components state probability estimation more difficult in most cases. This paper presents a new approach for evaluating complex system availability under epistemic uncertainties, based on a combination of the Dempster-Shafer Theory (DST) and a dynamic Bayesian network (DBN). This combination is called a dynamic evidential network(DEN). DST is well known for its utility and purpose to express uncertain experts' judgments about components state beliefs for treating epistemic uncertainty. In addition, the dynamic evidential network makes it possible to propagate this uncertainty while taking into consideration dynamic evolution and the dependency between components using conditional mass tables. Finally, a case study is presented as a validation of this approach.