Hierarchical propagation of probabilistic and non-probabilistic uncertainty in the parameters of a risk model

被引：30
|
作者：
Pedroni, N. [1 ]
Zio, E. [1 ,2 ]
Ferrario, E. [2 ]
Pasanisi, A. [3 ]
Couplet, M. [3 ]
机构：
[1] Politecn Milan, Dept Energy, I-20133 Milan, Italy
[2] Ecole Cent Paris, F-92295 Chatenay Malabry, France
[3] Elect France, Chatou, France
来源：
COMPUTERS & STRUCTURES | 2013年 / 126卷
关键词：
Hierarchical uncertainty; Possibility distributions; Fuzzy interval analysis; Two-level Monte Carlo method; Dependences; Flood protection dike; JOINT PROPAGATION; ADDRESSING UNCERTAINTY; EPISTEMIC UNCERTAINTY; MONTE-CARLO; FUZZY; REPRESENTATIONS; RELIABILITY; LEVEL-1;
D O I：
10.1016/j.compstruc.2013.02.003
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
We consider a model for the risk-based design of a flood protection dike, and use probability distributions to represent aleatory uncertainty and possibility distributions to describe the epistemic uncertainty associated to the poorly known parameters of such probability distributions. A hybrid method is introduced to hierarchically propagate the two types of uncertainty, and the results are compared with those of a Monte Carlo-based Dempster-Shafer approach employing independent random sets and a purely probabilistic, two-level Monte Carlo approach: the risk estimates produced are similar to those of the Dempster-Shafer method and more conservative than those of the two-level Monte Carlo approach. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码：199 / 213
页数：15
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