堆叠长期和短期记忆 (SLSTM) -辅助太赫兹光谱学结合变的重要性,用于快速识别红葡萄酒品种
Jingxiao Yu1, Hongbin Pu1, Da-Wen Sun2
1School of Food Science and Engineering, South China University of Technology, Guangzhou 510641, China; Academy of Contemporary Food Engineering, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China; Engineering and Technological Research Centre of Guangdong Province on Intelligent Sensing and Process Control of Cold Chain Foods, & Guangdong Province Engineering Laboratory for Intelligent Cold Chain Logistics Equipment for Agricultural Products, Guangzhou Higher Education Mega Centre, Guangzhou 510006, China.
太赫兹时域光谱 (THz-TDS) 与深度学习 (DL) 结合,可以准确识别红葡萄酒品种,防止错误标签. 这种新的方法提供了一种快速,非破坏性的方法来保护消费者和市场完整性.
科学领域:
- 光谱学和分析化学 分析化学
- 人工智能和机器学习
背景情况:
- 红葡萄酒的错误标签给消费者带来了重大风险.
- 传统的葡萄酒真实性的检测方法有限.
- 新技术对于准确的葡萄酒品种识别至关重要.
研究的目的:
- 开发一种快速,非破坏性的方法来区分红葡萄酒品种.
- 为了解决传统感官和化学分析的局限性.
- 为了打击葡萄酒产品的欺诈性错误标签.
主要方法:
- 太赫兹时域光谱学 (THz-TDS) 用于光谱数据采集.
- 深度学习 (DL) 模型,包括堆叠的长期和短期记忆 (SLSTM),被用于分类.
- 研究了第一个衍生谱和特征选择 (FS),以优化模型性能.
主要成果:
- 使用第一个衍生谱的SLSTM模型实现了高精度 (85.61%) 和性能指标.
- 具有换重要性 (PI) 的特征选择略有降低了准确性,但预测时间减少了2秒.
- 通过THz-TDS和DL方法,红葡萄酒标签显示出强大的歧视能力.
结论:
- 与DL结合的THz-TDS提供了一种新的,有效的解决方案,用于验证红葡萄酒品种的真实性.
- 该SLSTM模型提供了一个可靠的工具,用于快速和非破坏性的葡萄酒标签歧视.
- 这项技术支持市场的完整性,并保护消费者对葡萄酒欺诈的权利.
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