Parametric sensitivity analysis of precipitation and temperature based on multi-uncertainty quantification methods in the Weather Research and Forecasting model SCIENCE CHINA Earth Sciences 60, 876 (2017); The CDF and its sensitivity analysis of stochastic structure with stochastic excitation by advanced stratified line sampling

To fully analyze the effects of input variables on failure probability in reliability, an extended moment-independent importance measure based on the traditional moment-independent one is proposed. The computational cost of the moment-independent important measure is too high as direct Monte Carlo simulation is used. To overcome the difficulty, an integral solution is established by combining the highly efficient and exact Kernel density estimation. Results of several examples are used to demonstrate that the proposed importance measure can describe the effects of input variables on failure probability more fully and the established method can overcome the problem of "curse of dimensionality", which reduces the computational cost significantly.

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