Uncertainty Estimation for Empirical Signal Validation Modeling

机译：经验信号验证建模的不确定性估计

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Empirical modeling techniques have been applied to on-line process monitoringrnto detect equipment and instrumentation degradations. However, few applicationsrnprovide prediction uncertainty estimates, which can provide a measure of confidence inrnyour decisions. This paper presents the development of analytical prediction intervalrnestimate methods for three common non-linear empirical modeling strategies: artificialrnneural networks (ANN), neural network partial least squares (NNPLS), and localrnpolynomial regression (LPR). The techniques are applied to nuclear power plantrnoperational data for sensor calibration monitoring and verified via bootstrap simulationrnstudies.

机译：经验建模技术已应用于在线过程监控，以检测设备和仪器的性能下降。但是，很少有应用程序提供预测不确定性估计，这可以提供对决策的置信度的度量。本文介绍了三种常见的非线性经验建模策略的分析预测区间估计方法的发展：人工神经网络（ANN），神经网络偏最小二乘（NNPLS）和局部多项式回归（LPR）。该技术被应用于核电厂的运行数据，以进行传感器校准监控，并通过自举仿真研究进行验证。

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来源
《American Nuclear Society 4th international topical meeting on nuclear plant instrumentation, control and human machine interface technology (NPIC amp; HMIT 2004)》|2004年|1-13|共13页
会议地点 Columbus OH(US);Columbus OH(US)
作者
Brandon Rasmussen; J. Wesley Hines;
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作者单位

The University of Tennessee Knoxville, TN 37771 brandonprasmussen@yahoo.com;

The University of Tennessee Knoxville, TN 37771 jhines2@utk.edu;

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原文格式 PDF
正文语种 eng
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关键词
Empirical Modeling; Signal Validation; Uncertainty;

机译：实证模型；信号验证；不确定;

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专利

1. UNCERTAINTY ANALYSIS AND VALIDATION OF ENVIRONMENTAL MODELS - THE EMPIRICALLY BASED UNCERTAINTY ANALYSIS [J] . Monte L., Bergstrom U., Brittain J., Ecological Modelling . 1996,第1a3期

机译：环境模型的不确定性分析和验证-基于经验的不确定性分析
2. Mathematical models help explain experimental data. Response to 'Transcriptional interpretation of Shh morphogen signaling: computational modeling validates empirically established models' [J] . Cohen Michael, Page Karen M., Perez-Carrasco Ruben, Development . 2016,第10期

机译：数学模型有助于解释实验数据。对“ Shh形态发生子信号的转录解释：计算模型验证了经验建立的模型”的回应
3. Transcriptional interpretation of Shh morphogen signaling: computational modeling validates empirically established models [J] . Uhde Christopher W., Ericson Johan Development . 2016,第10期

机译：Shh形态发生子信号的转录解释：计算模型验证了经验建立的模型
4. Uncertainty Estimation for Empirical Signal Validation Modeling [C] . Brandon Rasmussen, J. Wesley Hines International Topical Meeting on Nuclear Plant Instrumentation, Control and Human Machine Interface Technololgy . 2004

机译：经验信号验证建模的不确定性估计
5. Prediction interval estimation techniques for empirical modeling strategies and their applications to signal validation tasks. [D] . Rasmussen, Brandon P. 2003

机译：用于经验建模策略的预测间隔估计技术及其在信号验证任务中的应用。
6. Reliable estimation of prediction errors for QSAR models under model uncertainty using double cross-validation [O] . Désirée Baumann, Knut Baumann 2014

机译：使用双重交叉验证可靠地估计模型不确定性下QSAR模型的预测误差
7. Capacity Estimation Models for Work-zones Under Traffic Signal Influence and the Empirical Validation [O] . Chi-Hyun Shin 2013

机译：交通信号影响下工作区的容量估计模型及经验验证
8. Empirical Modeling of Steady-State Behavior of Linear and Nonlinear Systems with Application to Signal Validation: Topical Report [R] . Frei, Z. , Upadhyaya, B. R. 1987

机译：线性与非线性系统稳态行为的经验模型及其在信号验证中的应用：专题报告

Uncertainty Estimation for Empirical Signal Validation Modeling

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