期刊文献+
共找到1篇文章
< 1 >
每页显示 20 50 100
Study on Cluster Analysis Used with Laser-Induced Breakdown Spectroscopy
1
作者 何力骜 王茜蒨 +2 位作者 赵宇 刘莉 彭中 《Plasma Science and Technology》 SCIE EI CAS CSCD 2016年第6期647-653,共7页
Supervised learning methods(eg.PLS-DA,SVM,etc.) have been widely used with laser-induced breakdown spectroscopy(LIBS) to classify materials;however,it may induce a low correct classification rate if a test sample ... Supervised learning methods(eg.PLS-DA,SVM,etc.) have been widely used with laser-induced breakdown spectroscopy(LIBS) to classify materials;however,it may induce a low correct classification rate if a test sample type is not included in the training dataset.Unsupervised cluster analysis methods(hierarchical clustering analysis,K-means clustering analysis,and iterative self-organizing data analysis technique) are investigated in plastics classification based on the line intensities of LIBS emission in this paper.The results of hierarchical clustering analysis using four different similarity measuring methods(single linkage,complete linkage,unweighted pair-group average,and weighted pair-group average) are compared.In K-means clustering analysis,four kinds of choosing initial centers methods are applied in our case and their results are compared.The classification results of hierarchical clustering analysis,K-means clustering analysis,and ISODATA are analyzed.The experiment results demonstrated cluster analysis methods can be applied to plastics discrimination with LIBS. 展开更多
关键词 unsupervised learning methods cluster analysis laser-induced breakdown spectroscopy(LIBS)
在线阅读 下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部