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矽肺病人发元素谱的Q型逐次信息群分
Q-TYPE STEPWISE INFORMATIONAL CLUSTER ANALYSIS FOR THE ELEMENTS TABLE OF SILICOTICS
【摘要】 用Q型逐次信息群分对白银矿区42名矽肺患者和41名正常人头发样的元素谱Cr、Zn、Mg、Al、Cd进行无监督模式识别,获得分类清晰的谱系图,83个样本的判别正确率达98.8%。这一结果表明,元素谱的Q型逐次信息群分可望成为研究和预测矽肺病的一种新技术。
【Abstract】 Unsupervised pattern recognition for the elements table, Cr,Zn,Mg,Al,Cd, in the hair species of the 42 silicotics and the 41 others in Baiyin diggings has been performed with Q-typestepwise informational cluster analysis and clearly classified dendrograms has been given out, in which, the accuracy is 98.8%. The results indicate that Q-type stepwise informational cluster analysis for the microelements table may be used as a new technique to research and predict anthrasilicosis.
【关键词】 聚类分析;
信息量;
模式识别;
矽肺病;
元素谱;
【Key words】 Cluster analysis; Information content; Pattern recognition; Anthrasilicosis; Elements table;
【Key words】 Cluster analysis; Information content; Pattern recognition; Anthrasilicosis; Elements table;
【基金】 甘肃省自然科学基金资助项目
- 【文献出处】 计算机与应用化学 ,Computers and Applied Chemistry , 编辑部邮箱 ,1995年04期
- 【分类号】R311
- 【下载频次】11