Data Comparison with Many Degrees of Freedom: the FSV (Feature Selective Validation) in Multiple Dimensions

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

Abstract

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.
多自由度数据比较:多维特征选择验证(FSV)
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。
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