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A new methodology based on covariance and HDMR for global sensitivity analysis

机译:基于协方差和HDMR的全局灵敏度分析新方法

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摘要

To execute variance based global sensitivity analysis efficiently and purposefully, a computing methodology containing two covariance methods is proposed. The first method estimates sensitivity indices by making full use of a sampling matrix and a re-sampling matrix. The second one is proposed for compensating the systematic error of the first method. Sources of error of the two methods become clear when utilizing high-dimensional model representation technique, then the application scope is obtained and verified by test examples, and it can help researchers choose an appropriate method according to the size of sensitivity index of a given variable. Compared with other sampling-based methods, the new methodology is proved to be efficient and robust by examples.
机译:为了有效,有目的地进行基于方差的全局敏感性分析,提出了一种包含两种协方差方法的计算方法。第一种方法通过充分利用采样矩阵和重采样矩阵来估计灵敏度指标。提出第二种方法是为了补偿第一种方法的系统误差。当利用高维模型表示技术时,这两种方法的误差源变得很清楚,然后通过测试实例获得并验证了其应用范围,可以帮助研究人员根据给定变量的敏感度指标的大小选择合适的方法。 。与其他基于采样的方法相比,通过实例证明了该新方法的有效性和鲁棒性。

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