An effective MIIMSDP(moment-independent importance measure and state dependent parameter) solution when failure state is fuzzy

Sections 1 through 3 of the full paper explain the MIIHSDP solution method mentioned in the title, which we believe is effective and whose core consists of; "For analyzing the effect of input variables on fuzzy failure probability when failure state is fuzzy, the difference between the conditional fuzzy failure probability and unconditional one is employed to define a moment-independent importance measure index. The effect of the input variables on the fuzzy failure probability can be measured quantitatively by the defined index. An analytical transformation is presented to reveal the inherent relation between the defined index and corresponding variance-based importance measure index, on which the defined moment-independent importance measure is transformed to the variance-based one of fuzzy failure state membership function. Based on this transformation and the state dependent parameter (SDP) model, the SDP method is established to estimate the defined moment-independent importance measure index, which can reduce the computational cost effectively. ". Section 3 presents two numerical examples, each of which uses three different kinds of membership function forms. These results, presented in Tables 1 and 2, and their a-nalysis demonstrate preliminarily the feasibility and rationality of the defined moment-independent importance measure index and the efficiency and precision of our SDP method.