A new algorithm for importance analysis of the inputs with distribution parameter uncertainty
| Autor: | Zhenzhou Lu, Luyi Li |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
021110 strategic
defence & security studies Mathematical optimization 021103 operations research Computation Monte Carlo method 0211 other engineering and technologies Sampling (statistics) Probability density function 02 engineering and technology Computer Science Applications Theoretical Computer Science Control and Systems Engineering Robustness (computer science) Probability distribution Sensitivity analysis Algorithm Uncertainty analysis Mathematics |
| Zdroj: | International Journal of Systems Science. 47:3065-3077 |
| ISSN: | 1464-5319 0020-7721 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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