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Modeling the Organoleptic Properties of Matured Wine Distillates

机译:模拟成熟酒馏分的感官特性

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摘要

We present how the supervised machine learning techniques can be used to predict quality characteristics in an important chemical engineering application: the wine distillate maturation process. A number of experiments have been conducted with six regression-based algorithms, where the M5' algorithm was proved to be the most appropriate for predicting the organoleptic properties of the matured wine distillates. The rules that are exported by the algorithm are as accurate as human expert's decisions.
机译:我们将介绍如何将监督的机器学习技术用于预测重要化学工程应用中的质量特征:葡萄酒馏出物的成熟过程。已经使用六种基于回归的算法进行了许多实验,其中M5'算法被证明最适合预测成熟酒馏分的感官特性。该算法导出的规则与人类专家的决策一样准确。

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