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Optimal Uncertainty Quantification

http://www.firstlight.cn2010/11/29

[作者] Houman Owhadi Clint Scovel Timothy John Sullivan

[单位] California Institute of Technology

[摘要] We propose a rigorous framework for Uncertainty Quantification (UQ) in which the UQ objectives and the assumptions/information set are brought to the forefront.

[关键词] Optimal Uncertainty Quantification

We propose a rigorous framework for Uncertainty Quantification (UQ) in which

the UQ objectives and the assumptions/information set are brought to the forefront.

This framework, which we call Optimal Uncertainty Quantification (OUQ), is based

on the observation that, given a set of assumptions and information about the problem,

there exist optimal bounds on uncertainties: these are obtained as extreme

values of well-defined optimization problems corresponding to extremizing probabilities

of failure, or of deviations, subject to the constraints imposed by the scenarios

compatible with the assumptions and information. In particular, this framework

does not implicitly impose inappropriate assumptions, nor does it repudiate relevant

information.

存档附件原文地址

原文发布时间:2010/9/26

引用本文:

Houman Owhadi;Clint Scovel;Timothy John Sullivan.Optimal Uncertainty Quantification http://ynufe.firstlight.cn/View.aspx?infoid=991679&cb=wxm2010
发布时间:2010/9/26.检索时间:2024/12/15

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