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A new computational method of a moment-independent uncertainty importance measure · Study

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ArticleA new computational method of a moment-independent uncertainty importance measure

Qiao Liu2008

Article2008

A new computational method of a moment-independent uncertainty importance measure

Qiao Liu · Toshimitsu Homma

137 citations·0/0 files stored·Reliability Engineering & System Safety

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Probabilistic and Robust Engineering Design Reliability and Maintenance Optimization Risk and Safety Analysis

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References

1981On The Quantitative Definition of Risk 1999A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output 2002Making best use of model evaluations to compute sensitivity indices 1996Importance measures in global sensitivity analysis of nonlinear models 2002Sensitivity Analysis for Importance Assessment 2006Survey of sampling-based methods for uncertainty and sensitivity analysis 2006A new uncertainty importance measure 1993Uncertainty and sensitivity analysis techniques for use in performance assessment for radioactive waste disposal

Cited by

2012Monte Carlo simulation for moment-independent sensitivity analysis 2014Polynomial chaos expansions for uncertainty propagation and moment independent sensitivity analysis of seawater intrusion simulations 2018Tree-based ensemble methods for sensitivity analysis of environmental models: A performance comparison with Sobol and Morris techniques 2012Sampling strategies in density-based sensitivity analysis 2014A new method for evaluating Borgonovo moment-independent importance measure with its application in an aircraft structure

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Details

Year2008

Typearticle

Published2008-11-08

VenueReliability Engineering & System Safety

ISSN-L0951-8320

Languageen

Citations137

Files0 public / 0

ShelfProbabilistic and Robust Engineering Design

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doi10.1016/j.ress.2008.10.005

openalex_workW2014017759

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2020A variable and mode sensitivity analysis method for structural system using a novel active learning Kriging model

2017Borgonovo moment independent global sensitivity analysis by Gaussian radial basis function meta-model

2016A hybrid approach for global sensitivity analysis