Input uncertainty in outout analysis

Input uncertainty in outout analysis
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输出分析中的输入不确定性

DOI:
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发表时间:
2012
期刊:
Online World Conference on Soft Computing in Industrial Applications
影响因子:
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通讯作者:
R. Barton
R. Barton
中科院分区:
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文献类型:
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作者:
R. Barton

文献摘要

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仿真输出显然取决于用于驱动模型的输入分布的形式。通常,这些输入分布是使用现实世界数据的有限样本来拟合的。样本的有限性会在输入分布中引入误差,从而影响输出。然而,在模拟输出分析中很少考虑输入模型不确定性到输出不确定性的传播。本教程以过去二十年提出的输入不确定性方法为背景,讨论了输入不确定性问题和最近开发的方法。
Simulation output clearly depends on the form of the input distributions used to drive the model. Often these input distributions are fitted using finite samples of real-world data. The finiteness of the samples introduces errors in the input distributions, affecting the output. Yet this propagation of input model uncertainty to output uncertainty is rarely considered in simulation output analysis. This tutorial presents a discussion of input uncertainty issues and recently developed methodological approaches, set in the context of input uncertainty methods proposed over the past twenty years.