基于Bayes-模糊逻辑算子的小子样可靠性信息融合方法

为了解决航空航天复杂系统可靠性评定中样本量小而导致评估结果可信度不高的问题,引入模糊逻辑算子这一非线性模型对多源可靠性验前信息进行融合,并给出了其参数估计的第二类极大似然(ML-Ⅱ)估计方法,通过仿真示例说明了融合方法的有效性.

Small-sample reliability information fusion approach based on bayes-fuzzy logistic operator

In order to solve the problem that the confidence level of reliability assessment results for complex system in aero&aircraft fields is low when test data are small, a fusion method based on Fuzzy Aggregation Operator (FAO) is promoted, which is to fully embody the degree of redundancy and complementarity of information from multiple sources. The unknown parameter of the fusion operator is estimated by the second maximum likelihood estimation method (ML-II). Simulation example shows that the proposed method is effective.