• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Reliability Engineering & System Safety >Monte-Carlo based uncertainty analysis: Sampling efficiency and sampling convergence
【24h】

Monte-Carlo based uncertainty analysis: Sampling efficiency and sampling convergence

机译：基于蒙特卡洛的不确定性分析：采样效率和采样收敛

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Monte Carlo analysis has become nearly ubiquitous since its introduction, now over 65 years ago. It is an important tool in many assessments of the reliability and robustness of systems, structures or solutions. As the deterministic core simulation can be lengthy, the computational costs of Monte Carlo can be a limiting factor. To reduce that computational expense as much as possible, sampling efficiency and convergence for Monte Carlo are investigated in this paper. The first section shows that non-collapsing space-filling sampling strategies, illustrated here with the maximin and uniform Latin hypercube designs, highly enhance the sampling efficiency, and render a desired level of accuracy of the outcomes attainable with far lesser runs. In the second section it is demonstrated that standard sampling statistics are inapplicable for Latin hypercube strategies. A sample-splitting approach is put forward, which in combination with a replicated Latin hypercube sampling allows assessing the accuracy of Monte Carlo outcomes. The assessment in turn permits halting the Monte Carlo simulation when the desired levels of accuracy are reached. Both measures form fairly noncomplex upgrades of the current state-of-the-art in Monte-Carlo based uncertainty analysis but give a substantial further progress with respect to its applicability.
机译：自从65年前引入蒙特卡洛分析以来，它几乎已无处不在。它是许多评估系统，结构或解决方案的可靠性和健壮性的重要工具。由于确定性核心仿真可能很漫长，因此蒙特卡洛的计算成本可能是一个限制因素。为了尽可能减少计算开销，本文研究了蒙特卡洛的采样效率和收敛性。第一部分显示了非折叠式空间填充采样策略（此处以maximin和统一的拉丁超立方体设计进行说明），极大地提高了采样效率，并以较小的运行次数实现了所需的准确度。在第二部分中，证明了标准抽样统计数据不适用于拉丁文超立方体策略。提出了一种样本拆分方法，该方法与复制的拉丁超立方抽样相结合，可以评估蒙特卡洛结果的准确性。评估又可以在达到所需的精度水平时停止蒙特卡洛模拟。两种措施都构成了基于蒙特卡洛的不确定性分析的当前最新技术的相当复杂的升级，但是在适用性方面有了实质性的进一步进步。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号