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相关概念视频

End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

379
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
379

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相关实验视频

Updated: Jul 18, 2025

Deep Neural Networks for Image-Based Dietary Assessment
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基于TabNet-GRA的食品安全风险预测和视觉分析.

Yi Chen1, Hanqiang Li1, Haifeng Dou1

  • 1Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University, Beijing 100048, China.

Foods (Basel, Switzerland)
|August 26, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了TabNet-GRA,这是一种结合深度学习 (TabNet) 和灰色关系分析 (GRA) 的新方法,用于准确预测食品安全风险. 这种方法增强了早期危险检测和公共卫生保护.

关键词:
在 TabNet TabNet 里面.早期预警的早期警告.食品安全 食品安全灰色的关系分析.风险预测风险预测视觉分析 视觉分析

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科学领域:

  • 食品科学 食品科学 食品科学
  • 数据科学数据科学数据科学
  • 公共卫生 公共卫生

背景情况:

  • 有效的食品安全风险预测对于积极的危险控制至关重要.
  • 现有的方法可能缺乏复杂的食品安全数据所需的精度.
  • 及时发现食源性危害对于保护公共健康至关重要.

研究的目的:

  • 开发和验证一种新的食品安全风险预测方法,TabNet-GRA.
  • 将深度学习 (TabNet) 与灰色关系分析 (GRA) 整合起来,以提高风险评估.
  • 创建一个实用的系统,用于食品安全风险预测和可视化.

主要方法:

  • 灰色关系分析 (GRA) 用于从合检测数据计算综合风险值.
  • 使用检测数据和GRA衍生的风险值来训练TabNet深度学习模型.
  • 对其他六种模型进行了比较实验,以评估性能.

主要成果:

  • 与传统方法相比,基于TabNet的模型表现出优越的装配能力.
  • 成功实施了一个功能性食品安全风险预测和可视化系统 (FSRvis).
  • 一个关于肉制品的案例研究证实了该方法的有效性.

结论:

  • TabNet-GRA方法为准确的食品安全风险预测提供了一个强大的工具.
  • FSRvis系统为有针对性的风险评估提供了有价值的视觉分析.
  • 这种方法加强了食品安全和公共卫生保护的决策.