期刊论文

Research on geographical origin traceability of Coix seed based on a modified random forest algorithm

中文

轻工学报

2096-1553

2023

38

6

70-77

10.12187/2023.06.009

湖南省高新技术产业科技创新引领计划项目(科技攻关类)(2020SK2029) 湖南省教育厅科研优秀青年项目(22B0579)。

本校为第一机构

以9个产地的薏苡仁为研究对象,通过将激发-发射矩阵(EEM)荧光光谱与改进的随机森林算法结合以实现薏苡仁产地的溯源分析。其中,随机森林算法的改进主要包括两方面:一是通过主成分分析(PCA)方法降低EEM荧光光谱的维度;二...展开更多 以9个产地的薏苡仁为研究对象,通过将激发-发射矩阵(EEM)荧光光谱与改进的随机森林算法结合以实现薏苡仁产地的溯源分析。其中,随机森林算法的改进主要包括两方面:一是通过主成分分析(PCA)方法降低EEM荧光光谱的维度;二是利用网格筛选法找出PCA降维过程中最优保留主成分数及判别模型超参数。结果表明:基于薏苡仁的EEM荧光光谱数据构建的改进随机森林模型(加入标准差...

Coix seeds from 9 different origins were taken as the research object.An attempt was made to achieve geographical origin traceability of Coix seeds through the combination of excitation-emission matrix(EEM)fluorescence spectroscopy with improved random forest algorithm....MORE Coix seeds from 9 different origins were taken as the research object.An attempt was made to achieve geographical origin traceability of Coix seeds through the combination of excitation-emission matrix(EEM)fluorescence spectroscopy with improved random forest algorithm.The improvements to the random forest algorithm main...