An extension of Universal Generating Function in Multi-State Systems Considering Epistemic Uncertainties
An extension of Universal Generating Function in Multi-State Systems Considering Epistemic Uncertainties
复制标题
考虑认知不确定性的多态系统中通用生成函数的扩展
DOI：
10.1109/tr.2013.2259206
复制
发表时间：
2013-05
影响因子：
5.9
通讯作者：
Sébastien Destercke;M. Sallak
中科院分区：
文献类型：
--
作者：
Sébastien Destercke;M. Sallak
许多实用的方法和不同的途径已被提出来评估多状态系统（MSS）的可靠性措施。通用生成函数（UGF）方法，在1986年推出，被认为是一个非常有效的方法来评估不同类型的MSS的可用性。在本文中，我们提出了一个扩展的UGF方法考虑认知的不确定性。这种扩展的方法允许一个模型不知名的概率和转换率，或在一个单一的模型中的偶然性和认知的不确定性建模。它是基于使用的信念功能，这是一般模型的不确定性。我们还比较了这种扩展与UGF方法的基础上进行概率界的区间算术运算。
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.