多自由度数据比较:多维特征选择验证(FSV)

A. Duffy, Gang Zhang, H. Sasse
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引用次数: 1

摘要

仿真软件及其运行平台的不断创新导致了更容易获得的数据,以及探索被分析系统更广泛参数的数据。这方面的一个例子是数据,如表面电流或场在一个体积。随着数据自由度的增加,用户从视觉上评估任何比较的能力减弱了。描述了一种类似于可靠性函数的启发式方法FSV (Feature Selective Validation)。描述了它在多维数据中的应用,并介绍了它在瞬态或脉冲现象分析中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Comparison with Many Degrees of Freedom: the FSV (Feature Selective Validation) in Multiple Dimensions
Constant innovation in simulation software and the platforms on which this runs is resulting in much more readily available data, and data which explores a wider range of parameters of the systems being analyzed. An example of this is data such as surface currents or fields in a volume. As the degrees of freedom in the data increases, the ability of the user to visually assess any comparisons diminishes. The FSV (Feature Selective Validation) method, a Reliability-Function like heuristic is described. The application to multiple dimension data is described and application to analyzing transient or pulse phenomena is presented.
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