An extension of Universal Generating Function in Multi-State Systems Considering Epistemic Uncertainties

被引:46
|
作者
Destercke, Sebastien [1 ]
Sallak, Mohamed [1 ]
机构
[1] Univ Technol Compiegne, Res Ctr Royallieu, Dept Comp Engn, Compiegne, France
关键词
Belief functions theory; epistemic uncertainties; multi-state systems; random sets; CARLO-SIMULATION APPROACH; IMPRECISE MARKOV-CHAINS; RELIABILITY; PERFORMANCE;
D O I
10.1109/TR.2013.2259206
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Many practical methods and different approaches have been proposed to assess Multi-State Systems (MSS) reliability measures. The universal generating function (UGF) method, introduced in 1986, is known to be a very efficient way of evaluating the availability of different types of MSSs. In this paper, we propose an extension of the UGF method considering epistemic uncertainties. This extended method allows one to model ill-known probabilities and transition rates, or to model both aleatory and epistemic uncertainty in a single model. It is based on the use of belief functions which are general models of uncertainty. We also compare this extension with UGF methods based on interval arithmetic operations performed on probabilistic bounds.
引用
收藏
页码:504 / 514
页数:11
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