拉曼光谱结合光谱特征区间筛选算法快速定量鉴别植物调和油品质OA北大核心CSTPCD
Rapid Quantitative Authentication of Blended Vegetable Oil Quality by Raman Spectroscopy Coupled with a Selection Algorithm of Spectral Characteristic Intervals
本研究提出了一种基于拉曼光谱与光谱特征区间筛选算法实现植物调和油中高价值植物油含量快速定量检测的方法.首先,将粒子群优化(particle swarm optimization,PSO)算法与灰狼优化(grey wolf optimization,GWO)算法融合构建混合智能优化算法,即PSOGWO算法.其次,将PSOGWO与组合移动窗口(combined moving window,CMW)策略结合构建新型的拉曼光谱特征区间筛选算法,即PSOG…查看全部>>
In this study,a method for the rapid quantitative determination of the content of high-value vegetable oil in blended edible vegetable oils(BEVO)was proposed based on Raman spectroscopy and a selection algorithm of spectral characteristic intervals.First,the particle swarm optimization(PSO)and grey wolf optimization(GWO)algorithms were combined to develop a hybrid intelligent optimization algorithm called PSOGWO.Second,the PSOGWO algorithm and the combined m…查看全部>>
吴升德;姜鑫;李爱琴;郭志明;朱家骥
盐城市产品质量监督检验所,江苏 盐城 224056盐城工学院电气工程学院,江苏 盐城 224051盐城工学院电气工程学院,江苏 盐城 224051江苏大学食品与生物工程学院,江苏 镇江 212013盐城工学院电气工程学院,江苏 盐城 224051
轻工业
拉曼光谱植物调和油智能优化算法光谱特征区间筛选定量鉴别
Raman spectroscopyblended edible vegetable oilsintelligent optimization algorithmsspectral characteristic intervals selectionquantitative authentication
《食品科学》 2024 (6)
244-253,10
国家自然科学基金青年科学基金项目(32102075)江苏省市场监督管理局科技计划项目(KJ2022050)江苏省高等学校基础科学(自然科学)面上项目(21KJD550002)
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