基于LDA降维方法的腹泻性贝类毒素检测研究

熊建芳; 刘瑶; 乔付; 刘忠艳; 姜微; 卢利琼

doi:10.13873/J.1000-9787(2023)05-0025-04

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基于LDA降维方法的腹泻性贝类毒素检测研究

研究与探讨 | 更新时间：2025-09-11

- 基于LDA降维方法的腹泻性贝类毒素检测研究
- 暂无标题
- 传感器与微系统 2023年第5期页码：25-28
- 作者机构：
  
  1. 岭南师范学院计算机与智能教育学院
  2. 岭南师范学院电子与电气工程学院
- 作者简介：
- 基金信息：
  
  国家自然科学基金青年科学基金资助项目(62005109);广东省自然科学基金面上资助项目(2020A515011368);广东省教育厅普通高校特色创新项目(2021KTSCX065);广东省教育科学规划项目(高等教育专项：2022GXJK256);2022年度岭南师范学院科研创新团队基金资助项目(XJ2022000501);岭南师范学院红树林研究院开放项目(PYXM04);广东省湛江市科技发展专项资金竞争性分配项目(2022A01005)
- DOI：10.13873/J.1000-9787(2023)05-0025-04
  中图分类号： O433;TP18;TS254.7
- 纸质出版：2023
- 稿件说明：
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熊建芳, 刘瑶, 乔付, 等. 基于LDA降维方法的腹泻性贝类毒素检测研究[J]. 传感器与微系统, 2023,(5):25-28.
熊建芳, 刘瑶, 乔付, 等. 基于LDA降维方法的腹泻性贝类毒素检测研究[J]. 传感器与微系统, 2023,(5):25-28. DOI： 10.13873/J.1000-9787(2023)05-0025-04.

DOI：

摘要

提出应用近红外(NIR)技术结合线性判别分析(LDA)方法和机器学习算法，对被腹泻性毒素污染贝类进行快速无损检测的新方法。首先，采集贻贝样本NIR光谱；然后，采用LDA对NIR光谱数据降维；最后，分别应用K近邻(KNN)、随机森林(RF)、极端梯度提升和逻辑回归(LR)4种算法实现腹泻性毒素污染贻贝分类检测。被腹泻性毒素污染的贻贝和健康贻贝的混合近红外光谱数据集经LDA降维后，使用4种分类器进行检测，准确率均达到100.00%。

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