Identification Influential Uncertainties in Monte Carlo Analysis

摘要

Monte Carlo simulation is a powerful and a practical tool for evaluating nonlinear systems. Its advantage is that it allows the effects of combinations of uncertainties to be taken into account. When the result of a Monte Carlo simulation is unsatisfactory, further investigations of both the system model and the control system are necessary, and it is important to identify those uncertain parameters that significantly influence the outcome of the simulation. However, the influential parameters are usually difficult to identify because multiple uncertain parameters are Incorporated into a simulation simultaneously.