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Use of Modern Regression Analysis in the Dielectric Properties of Foods

机译:现代回归分析在食品的介电特性中

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摘要

The dielectric properties of food materials is used to describe the interaction of foods with electromagnetic energy for food technology and engineering. To quantify the relationship between dielectric properties and influencing factors, regression analysis is used in our study. Many linear or polynomial regression equations are proposed. However, the basic assumption of the regression analysis is that data with a normal distribution and constant variance are not checked. This study uses sixteen datasets from the literature to derive the equations for dielectric properties. The dependent variables are the dielectric constant and the loss factor. The independent variables are the frequency, temperature, and moisture content. The dependent variables and frequency terms are transformed for regression analysis. The effect of other qualitative factors, such as treatment method and the position of subjects on dielectric properties, are determined using categorical testing. Then, the regression equations can be used to determine which influencing factors are important and which are not. The method can be used for other datasets of dielectric properties to classify influencing factors, including quantitative and qualitative variables.
机译:食品材料的介电性质用于描述食品与食品技术和工程电磁能的相互作用。为了量化介电性质与影响因子之间的关系,我们的研究使用了回归分析。提出了许多线性或多项式回归方程。然而,回归分析的基本假设是没有检查具有正常分布和恒定方差的数据。本研究使用来自文献的十六个数据集来导出介电特性的方程。从属变量是介电常数和损耗因子。独立变量是频率,温度和含水量。因回归分析转换了所属变量和频率术语。使用分类测试确定其他定性因素的影响,例如治疗方法和受试者对电介质性质的位置。然后,回归方程可用于确定哪些影响因素是重要的,哪些影响因素是不是。该方法可用于介电性质的其他数据集以对影响因素进行分类,包括定量和定性变量。

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