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Illustrating the Future Prediction of Performance Based on Computer Code,Physical Experiments, and Critical Performance Parameter Samples

机译:基于计算机代码,物理实验和关键性能参数样本说明性能的未来预测

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In this article, we present a generic example to illustrate various points about making future predictions of population performance using a biased performance computer code, physical performance data, and critical performance parameter data sampled from the population at various times. We show how the actual performance data help to correct the biased computer code and the impact of uncertainty, especially when the prediction is made far from where the available data are taken. We also demonstrate how a Bayesian approach allows both inferences about the unknown parameters and predictions to be made in a consistent framework.
机译:在本文中,我们将提供一个通用示例,说明有关使用偏向性能计算机代码,物理性能数据和在各个时间采样的关键性能参数数据对人口性能进行未来预测的各个方面。我们将展示实际性能数据如何帮助纠正有偏见的计算机代码和不确定性的影响,尤其是在远离可用数据的预测位置进行预测时。我们还演示了贝叶斯方法如何允许在一致的框架中进行有关未知参数的推断和预测。

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