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基于颜色量化和机器学习的烟草化学成分在固化过程中的回归预测

Yang Meng1, Qiang Xu1, Guangqing Chen2

  • 1Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou, 450001, China.

Scientific reports
|November 7, 2024
PubMed
概括

这项研究表明,使用机器学习,烟草叶的颜色可以准确地预测水分,糖和粉等关键化学成分. 这允许在烟草固化过程中实时进行质量监测.

关键词:
化学元件 化学元件 化学元件颜色值 颜色值 的颜色值.机器学习算法 机器学习算法预测模型的预测模型.烟草化 烟草化

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Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
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