混凝土和骨料性能评价中的多元统计方法

P. Hudec
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引用次数: 0

摘要

简单的单变量统计分析,如均值、标准差、双变量回归和相关等,在混凝土技术中得到了广泛的应用。然而,它们一次只能给出最多涉及两个变量的结果。在现实世界中,强度、抗冻性、碱反应性等性能取决于几个相互依赖的变量。例如,聚类分析等多元统计技术可以将具有相似属性的所有聚合分组;因子分析可以分辨出哪种测试组合最能描述混凝土的期望性能,逐步回归分析可以用来预测基于几个标准测试的混凝土或骨料的使用能力(项目寿命)。上述统计技术的例子以非技术形式呈现,基于对混凝土骨料性能与其服务记录相关的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multivariate Statistical Methods in Evaluation of Concrete and Aggregate Properties
Simple univariate statistical analyses such as mean, standard deviation, and bivariate regression, and correlation etc. are in widespread use in concrete technology. However, they only give results concerning at most two variables at a time. In the real world, the properties such as strength, frost resistance, alkali reactivity, etc. depend on several mutually dependent variables. For instance, multivariate statistical techniques such as cluster analysis can group all aggregates with similar properties; factor analysis can discern what combination of tests best describe a desired property of concrete, and stepwise regression analysis can be used to predict serviceability (project life) of concrete or aggregate based on several standard tests. Examples of the above statistical techniques are presented in a non-technical format, based on research into concrete aggregate properties as related to their service record.
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