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Absstract of: CN118428797A
本发明属于酿酒以及高温大曲品质评价技术领域,涉及一种基于多维度的高温大曲后熟综合品质的评价方法。所述评价方法包括如下步骤:(1)获取所述高温大曲对应的特征性评价指标;(2)对各特征性评价指标进行标准化处理,获得各特征性评价指标对应的标准化值;再基于所述标准化值对各特征性评价指标对应的权重值进行计算,获得各特征性评价指标对应的权重值;(3)基于所述标准化值以及权重值,运用多因子模糊数学综合评定法对所述高温大曲的后熟综合品质进行评估计算,得到所述高温大曲的后熟综合品质的评价结果,基于所述评价结果对所述高温大曲的后熟综合品质进行评价。本发明所提供的评价方法可对高温大曲不同储存期限的后熟综合品质实现准确、客观地评价。
Nº publicación: CN118435202A 02/08/2024
Applicant:
华为云计算技术有限公司
Absstract of: WO2023117070A1
A modelling and/or prediction apparatus (1900) for calibrating a set of one or more models (321) of a physical system, the modelling and/or prediction apparatus (1900) comprising one or more processors (1901) and a memory (1902) storing in non-transient form data defining program code executable by the one or more processors (1901), wherein the program code, when executed by the one or more processors (1901), causes the modelling and/or prediction apparatus (1900) to: obtain the set of one or more models (321) of the physical system; obtain real-world data (310) from the physical system for one or more scenarios; obtain rules (322) about the physical system operation; and calibrate the set of one or more models (321) of the physical system using machine learning to fit the real-world data (310) from the physical system and in dependence on the rules (322) about the physical system. By using the rules (322) the calibrated model (321) may produce more accurate and realistic results.