食品与机械2024，Vol.40Issue(10)：53-61,9.DOI:10.13652/j.spjx.1003.5788.2024.60122
基于三维荧光光谱和ISSA-SVM的食用植物油鉴别
Classification of edible vegetable oils based on three-dimensional fluorescence spectroscopy and ISSA-SVM
摘要
Abstract
[Objective]To improve the classification accuracy of edible vegetable oils,an identification model based on three-dimensional fluorescence spectroscopy and ISSA-SVM was established.[Methods]Combining the feature information of three-dimensional fluorescence spectroscopy,an improved sparrow search algorithm was used to optimize the parameters of the SVM model,constructing an edible vegetable oil identification method that integrates the characteristics of three-dimensional fluorescence spectroscopy information and the ISSA-SVM model.[Results]Compared with the SVM model,GA-SVM model,PSO-SVM model,and SSA-SVM model,the classification accuracy of the ISSA-SVM model for edible vegetable oils reached 100%.[Conclusion]The ISSA-SVM model has higher convergence efficiency,system stability,and the ability to avoid local optimal solutions,which can effectively cope with complex and variable sample classification tasks.关键词
支持向量机/麻雀搜索算法/三维荧光光谱/食用植物油Key words
support vector machine/sparrow search algorithm/three-dimensional fluorescence spectroscopy/edible vegetable oils引用本文复制引用
张静,齐国红,陈景召,曹晓丽,李莉莉..基于三维荧光光谱和ISSA-SVM的食用植物油鉴别[J].食品与机械,2024,40(10):53-61,9.基金项目
河南省科技厅科技攻关项目(编号:232102221029) （编号:232102221029）
河南省教育厅高校品牌专业建设项目(编号:教政法[2016]896号) （编号:教政法[2016]896号）
