Graduation formula: a new method to construct belief reliability distribution under epistemic uncertainty

In reliability engineering,the observations of the variables of interest are always limited due to cost or schedule constraints.Consequently,the epistemic uncertainty,which derives from lack of knowledge and information,plays a vital influence on the reliability evaluation.Belief reliability is a new reliability metric that takes the impact of epistemic uncertainty into consideration and belief reliability distribution is fundamental to belief reliability application.This paper develops a new method called graduation formula to construct belief reliability distribution with limited observations.The developed method constructs the belief reliability distribution by determining the corresponding belief degrees of the observations.An algorithm is designed for the graduation formula as it is a set of transcendental equations,which is difficult to determine the analytical solution.The developed method and the proposed algorithm are illustrated by two numerical examples to show their efficiency and future application.

Uncertainty entropy-based exploratory evaluation method and its applications on missile effectiveness evaluation

Some attributes are uncertain for evaluation work because of incomplete or limited information and knowledge.It leads to uncertainty in evaluation results.To that end,an evaluation method,uncertainty entropy-based exploratory evaluation(UEEE),is proposed to guide the evaluation activities,which can iteratively and gradually reduce uncertainty in evaluation results.Uncertainty entropy(UE)is proposed to measure the extent of uncertainty.First,the belief degree distributions are assumed to characterize the uncertainty in attributes.Then the belief degree distribution of the evaluation result can be calculated by using uncertainty theory.The obtained result is then checked based on UE to see if it could meet the requirements of decision-making.If its uncertainty level is high,more information needs to be introduced to reduce uncertainty.An algorithm based on the UE is proposed to find which attribute can mostly affect the uncertainty in results.Thus,efforts can be invested in key attribute(s),and the evaluation results can be updated accordingly.This update should be repeated until the evaluation result meets the requirements.Finally,as a case study,the effectiveness of ballistic missiles with uncertain attributes is evaluated by UEEE.The evaluation results show that the target is believed to be destroyed.