失效概率估计的条件蒙特卡罗方法

A. Borodina, O. Lukashenko, E. Morozov
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引用次数: 2

摘要

我们考虑具有渐进和瞬时故障的系统,用所谓的退化过程来描述,退化过程由连续阶段的总和组成,其中预防性修复用于防止瞬时故障。失效概率的计算是这类系统最优控制中一个重要而又困难的问题。所需的性能度量通常无法分析得到。因此,必须依靠模拟技术。基于Asmussen和Kroese在b[1]中提出的算法,我们开发了一种方差缩减技术,利用条件蒙特卡罗方法估计目标失效概率。通过相对误差仿真验证了该方法的有效性。我们给出了一些数值结果,表明该方法提供了比较准确的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Conditional Monte Carlo for the Failure Probability Estimation
We consider the system with gradual and instantaneous failures described in terms of the so-called degradation process composed by a sum of the successive phases, where preventive repair is used to prevent an instantaneous failure. The calculating the failure probability is an important and hard problem, arising in the optimal control of such a systems. The required performance measure is usually not analytically available. Thus, one has to rely on simulation technique. We develop a variance reduction technique to estimate the target failure probability using a conditional Monte Carlo method is based on the algorithm proposed by Asmussen and Kroese in [1]. The effectiveness of the proposed approach is investigated through simulations in terms of relative error. We present a few numerical results which indicate that proposed approach provides comparatively accurate results.
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