基于多维极值参数的飞行风险量化评估方法

数具有和试验数据相同的分布形式,并构建了飞行风险发生的判定条件。在对一维极值参数符合广义极值分布的假设进行证明的基础上,提出了三维极值参数的四参数变权重(four adaptive weight parameters, FAWP),Copula模型利用自适应粒子群算法对一维和三维目标函数中的未知参数进行了辨识,对多种Copula辨识出的三维极值分布进行了拟合优度检验,结果表明FAWP Copula对三维极值参数分布形式的描述最为精确。利用FAWP Copula模型对尾流遭遇情形下的飞行风险概率进行了量化计算,所得指标可用来研究尾流场内的风险规避策略及算法。

Quantitative flight risk evaluation method based on multi-dimensional extreme parameters

A new flight risk assessment approach based on multidimensional extreme Copula is proposed using multivariate extreme value theory and coupled system modeling ideas. First, we extract three-dimensional wake extreme parameters required for assessing the risk using Monte Carlo method, verify the extracted extreme parameters and the test data has the same distribution form, then build a flight risk determination condition; Second, we propose the four adaptive weight parameters (FAWP) for three-dimensional extreme parameters based on the result that the one-dimensional extreme parameters meet generalized extreme value distribution; Third, adaptive range particle swarm optimization algorithm is used to identify unknown parameters of the one-dimensional and three-dimensional objective function. The results of fitting test show FAWP Copula model has higher accuracy than the other Copula models, so it is the most suitable model to describe the thick tail formed by multi-dimensional extreme values. At last, the risk probability in the situation of near-ground wake encounter is evaluated using FAWP Copula, and it has some certain reference values for research directions such as wake navigation control and risk aversion.