随机和认知混合不确定系统的全局灵敏度分析方法.

To compute the sensitivity of the hybrid uncertain system in which both aleatory and epistemic uncertainties are present, a global sensitivity analysis method is proposed on the basis of evidence theory and conditional probability theory. The aleatory uncertain variables are represented by using the evidence theory. For epistemic uncertain variable, two stochastic sampling approaches based on the evidence theory are put forward, which are named one-step and two-step random sampling approach, respectively. With the conditional probability theory and the Sobol, method used, the global sensitivity indexes of the hybrid uncertain system are proposed in the presence of epistemic uncertainties, and the formulas of the first-order and total sensitivity indexes are derived. A single-loop quasi-Monte Carlo simulation is developed and it is used to approximately calculate the sensitivity indexes proposed. The sensitivity analysis program based on Matlab is designed. A typical example is presented and its results show that the proposed method is correct and its computational cost is acceptable. [ABSTRACT FROM AUTHOR]