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首页> 外文期刊>Stochastic environmental research and risk assessment >Cokriging for multivariate Hilbert space valued random fields: application to multi-fidelity computer code emulation
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Cokriging for multivariate Hilbert space valued random fields: application to multi-fidelity computer code emulation

机译:多元希尔伯特空间值随机字段的协同克里格:在多保真度计算机代码仿真中的应用

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摘要

In this paper we propose Universal trace cokriging, a novel methodology for interpolation of multivariate Hilbert space valued functional data. Such data commonly arises in multi- fidelity numerical modeling of the subsurface and it is a part of many modern uncertainty quantification studies. Besides theoretical developments we also present methodological evaluation and comparisons with the recently published projection based approach by Bohorquez et al. (Stoch Environ Res Risk Assess 31(1): 53- 70, 2016. https://doi.org/10.1007/s00477-0161266-y).Our evaluations and analyses were performed on synthetic (oil reservoir) and real field (uranium contamination) subsurface uncertainty quantification case studies. Monte Carlo analyses were conducted to draw important conclusions and to provide practical guidelines for all future practitioners.
机译:在本文中,我们提出了通用迹线协同克里金法,一种用于对多元希尔伯特空间值函数数据进行插值的新方法。这种数据通常出现在地下的多保真度数值模​​拟中,并且是许多现代不确定性量化研究的一部分。除了理论上的发展,我们还介绍了方法论上的评估和与Bohorquez等人最近发表的基于投影的方法的比较。 (《斯托克环境风险评估》 31(1):2016年第53-70页.https://doi.org/10.1007/s00477-0161266-y)。我们对合成油藏和实际油田进行了评估和分析(铀污染)地下不确定性量化案例研究。进行了蒙特卡洛分析以得出重要结论并为所有未来的从业人员提供实用指南。

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