摘要
对 5个烟叶产区的 88个烟草样品 ,利用火焰光度法和原子吸收光谱法分别测定其钾和镁、钠、锰、铁和锌的含量 ,应用模糊c 均值 (FCM )聚类分析与系统聚类分析对这些样品分类。结果表明 ,模糊聚类分析对于烟草产地的判断具有积极的指导意义 。
The contents of potassium, magnesium, sodium, manganese, ferrum and zinc were determined by flame spectrometry and atomic absorption spectrometry respectively. The dataset was clustered by fuzzy c-means (FCM) clustering analysis and hierarchical clustering analysis. It is shown that the results of the FCM clustering analysis are more accurate than those of the hierarchical cluster analysis, and it is with positive meaning to apply FCM clustering analysis to estimating the producing area of tobaccos.
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2004年第8期1009-1012,共4页
Spectroscopy and Spectral Analysis
基金
国家烟草专卖局科技攻关项目 (1 1 0 2 2 0 1 0 1 0 1 6)资助
