| 补益中药材药效计算机分类法研究 |
| |
| 引用本文： | 郑育平.补益中药材药效计算机分类法研究[J].广东微量元素科学,2004,11(3):31-36. |
| |
| 作者姓名： | 郑育平 |
| |
| 作者单位： | 广东医学院附属医院,广东,湛江,524001 |
| |
| 摘 要： | 根据计算机模式识别法的马氏(Mahalanobis)距离判别法原理，用Visual Basic语言编制应用程序软件系统，对补气、补阳、补阴和补血等四类补益中药材中的十二种矿物元素谱进行分类判别研究。当选择Sr、Cr、Co、Ni、Mn、Cu、Zn、Fe、Na、Ca等元素为特征参量，将药材中这些无机元素含量值作为客观指标，可准确地对四类补益药进行分类鉴别。训练样本的学习准确识别率为94．7％，待判补益中药的准确预报率为90.4％。本法为使用客观的检测指标，对中药材药效进行分类、鉴别提供了新的途径。
|
| 关 键 词： | 补益中药材 矿物元素 计算机模式识别技术 药效分类判别 |
| 文章编号： | 1006-446X(2004)03-0031-05 |
| 修稿时间： | 2004年2月1日 |
Study on Classfication of Efficacy of Benitit Traditional Chinese Medicine by Computer Pattern Recognition |
| |
| ZHENG Yu-ping.Study on Classfication of Efficacy of Benitit Traditional Chinese Medicine by Computer Pattern Recognition[J].Trace Elements Science,2004,11(3):31-36. |
| |
| Authors: | ZHENG Yu-ping |
| |
| Abstract: | Based on 12 mineral elements table,the classfication of the efficacy of benitit traditional Chinese medicine(TCM)was studied by computer pattern recognition(Mahalamobis distance desicion metnod).The result showed that when Sr,Cr,Co,Ni,Mn,Cu,Zn,Fe,Na,Ca were selected as the character parameter,the correct rate of judgement in training sample and in differentiated benifit TCM were 94 7% and 90 4% respectively. |
| |
| Keywords: | benifit traditional Chinese medicine mineral element computer pattern recognition |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
