To estimate accident probabilities for commercial
airlines, a sampling method called subset simulation
is used at the Institute of Flight System Dynamics.
Thereby, a physical model is utilized that
considers a set of contributing factors and returns
a so-called incident metric which describes the
criticality of the particular flight with respect to a
specific accident category. For accident probability
estimations, multiple high-dimensional samples, i.e. virtual flights are generated and the
physical model is applied for them. The goal
of this paper is to integrate vine copula dependence
models into the subset simulation implementation.
These mathematical dependence
models very flexibly describe high-dimensional
and non-linear dependencies between the contributing
factors. Eventually, the prevailing dependence
structures of the contributing factors
are recognized during the generation of the samples
leading to more realistic results.
«
To estimate accident probabilities for commercial
airlines, a sampling method called subset simulation
is used at the Institute of Flight System Dynamics.
Thereby, a physical model is utilized that
considers a set of contributing factors and returns
a so-called incident metric which describes the
criticality of the particular flight with respect to a
specific accident category. For accident probability
estimations, multiple high-dimensional samples, i.e. virtual flights a...
»