国防科技大学学报2017，Vol.39Issue(4)：154-160,7.DOI:10.11887/j.cn.201704024
多输出性能下的重要性测度指标及其求解方法
Global sensitivity analysis for multiple outputs and their solutions
摘要
Abstract
Aiming at solving the existing drawbacks of indices of the Mahalanobis distance, an importance measure based on the Moore-Penrose Mahalanobis distance weighted by spectral decomposition was proposed.Through building the generalized matrix inversion of covariance matrix of multi-output and the spectral decomposition, the problems that the covariance matrix was be inversed and misidentification for lacking the adequate consideration about the relation among the multiple outputs were solved.Thus, the limitations of indices of Mahalanobis distance were overcome.The results of numerical examples and engineer instance show that the proposed importance measurement can accurately get the effects of input variables on the integrated performance of multi-output structure system, thus providing effective information for reliability design.关键词
多输出/重要性测度/马氏距离/广义逆矩阵/谱分解加权Key words
multivariate output/importance measure/Mahalanobis distance/generalized inverse matrix/weighted spectral decomposition分类
通用工业技术引用本文复制引用
徐立扬,吕震宙,王飞,肖思男..多输出性能下的重要性测度指标及其求解方法[J].国防科技大学学报,2017,39(4):154-160,7.基金项目
国家自然科学基金资助项目(NSFC51475370) （NSFC51475370）
中央高校基本科研业务费专项资金资助项目(3102015BJ(Ⅱ)CG009) （3102015BJ(Ⅱ）
