Title
A new algorithm for importance analysis of the inputs with distribution parameter uncertainty.
Abstract
Importance analysis is aimed at finding the contributions by the inputs to the uncertainty in a model output. For structural systems involving inputs with distribution parameter uncertainty, the contributions by the inputs to the output uncertainty are governed by both the variability and parameter uncertainty in their probability distributions. A natural and consistent way to arrive at importance analysis results in such cases would be a three-loop nested Monte Carlo MC sampling strategy, in which the parameters are sampled in the outer loop and the inputs are sampled in the inner nested double-loop. However, the computational effort of this procedure is often prohibitive for engineering problem. This paper, therefore, proposes a newly efficient algorithm for importance analysis of the inputs in the presence of parameter uncertainty. By introducing a ‘surrogate sampling probability density function SS-PDF’ and incorporating the single-loop MC theory into the computation, the proposed algorithm can reduce the original three-loop nested MC computation into a single-loop one in terms of model evaluation, which requires substantially less computational effort. Methods for choosing proper SS-PDF are also discussed in the paper. The efficiency and robustness of the proposed algorithm have been demonstrated by results of several examples.
Year
DOI
Venue
2016
10.1080/00207721.2015.1088099
Int. J. Systems Science
Keywords
Field
DocType
importance analysis, input variable, parameter uncertainty, surrogate sampling function, single-loop Monte Carlo method
Mathematical optimization,Monte Carlo method,Sensitivity analysis,Algorithm,Uncertainty analysis,Robustness (computer science),Probability distribution,Sampling (statistics),Probability density function,Mathematics,Computation
Journal
Volume
Issue
ISSN
47
13
0020-7721
Citations 
PageRank 
References 
1
0.36
9
Authors
2
Name
Order
Citations
PageRank
Luyi Li1103.62
Zhenzhou Lu218233.11