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Titlebook: Uncertainty Quantification in Scientific Computing; 10th IFIP WG 2.5 Wor Andrew M. Dienstfrey,Ronald F. Boisvert Conference proceedings 201

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41#
發(fā)表于 2025-3-28 16:25:45 | 只看該作者
Efficient Computation of Observation Impact in 4D-Var Data Assimilation state of a physical system. Different observational data points have different contributions to reducing the uncertainty with which the state is estimated. Quantifying the observation impact is important for analyzing the effectiveness of the assimilation system, for data pruning, and for designing
42#
發(fā)表于 2025-3-28 19:36:15 | 只看該作者
43#
發(fā)表于 2025-3-29 02:41:29 | 只看該作者
Reducing the Uncertainty When Approximating the Solution of ODEs a more rigorous error control strategy and which deliver an approximate solution that is much more likely to satisfy the expectations of the user. We have developed such a class of ODE methods as well as a collection of software tools that will deliver a piecewise polynomial as the approximate solu
44#
發(fā)表于 2025-3-29 05:15:49 | 只看該作者
45#
發(fā)表于 2025-3-29 08:29:42 | 只看該作者
Conference proceedings 2012WoCoUQ 2011, held in Boulder, CO, USA, in August 2011. The 24 revised papers were carefully reviewed and selected from numerous submissions. They are organized in the following topical sections: UQ need: risk, policy, and decision making, UQ theory, UQ tools, UQ practice, and hot topics. The papers
46#
發(fā)表于 2025-3-29 15:11:50 | 只看該作者
47#
發(fā)表于 2025-3-29 16:22:35 | 只看該作者
Uncertainty and Sensitivity Analysis: From Regulatory Requirements to Conceptual Structure and Compuspace characterizing aleatory uncertainty, (ii) a probability space characterizing epistemic uncertainty, and (iii) a model that predicts system behavior. The presented approach is illustrated with results from the 2008 performance assessment for the proposed repository for high-level radioactive waste at Yucca Mountain, Nevada.
48#
發(fā)表于 2025-3-29 21:50:33 | 只看該作者
49#
發(fā)表于 2025-3-30 01:39:28 | 只看該作者
50#
發(fā)表于 2025-3-30 08:02:38 | 只看該作者
Considerations of Uncertainty in Regulatory Decision Makingcribes the Commission’s policy on the use of probabilistic methods to complement the more traditional deterministic approach, and identifies some example challenges as a staff group considers a strategic vision of how the agency should regulate in the future.
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