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dc.contributor.author章元
dc.contributor.author朱尔一
dc.contributor.author庄峙厦
dc.contributor.author李波
dc.contributor.author王小如
dc.date.accessioned2016-05-17T02:55:54Z
dc.date.available2016-05-17T02:55:54Z
dc.date.issued1998
dc.identifier.citation高等学校化学学报,1998,(7):49-51
dc.identifier.issn0251-0790
dc.identifier.otherGDXH807.010
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/107550
dc.description.abstract通过对人发样品中22种元素含量的数据进行变量扩维及压缩筛选处理,选出了影响性别判断较显著的变量,用PlS法处理这些变量组成的数据,得到男性与女性分类清晰的二维判别图及预报模型,并根据所建立的预报模型及人发微量元素的含量判别人的性别,准确率为81%.
dc.description.abstractThe data of 22 trace elements concentrations in human hair samples were obtained by ICP AES and GFAAS.The variables which have significant influence on discriminating the sex are selected through the treatment of the concentration data by the variable dimension expansion and the variable selection methods.The discrimination plane figure with the good classification is obtained through the treatment of the data with selected variables by PLS method.The prediction models are built and used to distinguish the human sex according to the element concentrations data in human hair.The accuracy of the prediction is 81%.
dc.description.sponsorship国家教育委员会留学回国人员科研启动费;福建省自然科学基金
dc.language.isozh_CN
dc.subject变量筛选
dc.subjectPLS回归
dc.subject微量元素
dc.subjectModel selection
dc.subjectPLS regression
dc.subjectTrace element
dc.title人发微量元素与性别关系的模式识别分类研究
dc.title.alternativeClassification Study by Pattern Recognition on the Relationship Between the Trace Elements in Human Hair and Sex
dc.typeArticle


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