首页 | 本学科首页   官方微博 | 高级检索  
     检索      

光谱结合主成分分析和模糊聚类方法的样品聚类与识别
引用本文:褚小立,袁洪福,陆婉珍.光谱结合主成分分析和模糊聚类方法的样品聚类与识别[J].分析化学,2000,28(4):421-427.
作者姓名:褚小立  袁洪福  陆婉珍
作者单位:北京石油化工科学研究院!北京,100083,北京石油化工科学研究院!北京,100083,北京石油化工科学研究院!北京,100083
摘    要:针对紫外光谱结合化学计量学方法快速测定渣油烃族组成模型适应性问题,对渣油光谱进行主成分分析,以主成分得分作为聚类的特征变量进行模糊聚类,建立了光谱结合主成分分析和模糊聚类方法的样品聚类与识别方法和识别,为光谱结合化学计量分析方法中构正模型的正确选择提供了依据。

关 键 词:渣油  紫外光谱  主成分分析  模糊聚类  模式识别

Samples Clustering and Recognition with Fuzzy Clustering and Principal Component Analysis Method in Spectral Analysis
Chu Xiaoli,Yuan Hongfu,Lu Wanzhen.Samples Clustering and Recognition with Fuzzy Clustering and Principal Component Analysis Method in Spectral Analysis[J].Chinese Journal of Analytical Chemistry,2000,28(4):421-427.
Authors:Chu Xiaoli  Yuan Hongfu  Lu Wanzhen
Abstract:A rapid method for clustering and recognizing the type of residues was developed based on fuzzyclustering and principal component analysis (PCA) with ultraviolet petra. By treatment with PCA, thequantitative information was obtained, and the number of characteristics for fuzzy clustering was reduced.Thismehod has been successfully applied to the rapid recognition of different types of residues, which will be thebois for predicting the hydrocarbon composition of residues with chemometrics methods. The method can alsobe applied to other spectra for clustering and recognition, and provides with foundation of choosing propercalibration models.
Keywords:Residues  ultraviolet spectra  principal component analysis  fuzzy clustering  pattern recognition
本文献已被 CNKI 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号