Computer model validation with functional output
具有函数型输出的计算机模型验证AI 解读 ↓
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具有函数型输出的计算机模型验证
- 研究问题
- 如何利用现场数据检验计算机模型是否充分反映现实，同时处理高度不规则的函数型输出和模型输入的不确定性？
- 方法与思路
- 作者将函数型数据表示为小波系数，在系数层面应用分层标量验证方法，再变换回原尺度比较模型与现场输出。
- 材料陈述的贡献
- 摘要称，该方法扩展既有验证流程以处理不规则函数数据和输入不确定性，并以工程系统的动态应力分析示例展示。
- 阅读关注点
- 应核对小波分解的选择、各类误差与不确定性的区分、分层模型设定，以及输入不确定性如何传递至输出比较。
- 阅读边界
- 仅据 OpenAlex 索引摘要，稿件版本未注明；摘要未提供验证阈值、计算成本或外推表现，其适用性受计算工具与分解方式限制。
原文摘要
A key question in evaluation of computer models is Does the computer model adequately represent reality? A six-step process for computer model validation is set out in Bayarri et al. [Technometrics 49 (2007) 138–154] (and briefly summarized below), based on comparison of computer model runs with field data of the process being modeled. The methodology is particularly suited to treating the major issues associated with the validation process: quantifying multiple sources of error and uncertainty in computer models; combining multiple sources of information; and being able to adapt to different, but related scenarios. Two complications that frequently arise in practice are the need to deal with highly irregular functional data and the need to acknowledge and incorporate uncertainty in the inputs. We develop methodology to deal with both complications. A key part of the approach utilizes a wavelet representation of the functional data, applies a hierarchical version of the scalar validation methodology to the wavelet coefficients, and transforms back, to ultimately compare computer model output with field output. The generality of the methodology is only limited by the capability of a combination of computational tools and the appropriateness of decompositions of the sort (wavelets) employed here. The methods and analyses we present are illustrated with a test bed dynamic stress analysis for a particular engineering system.