摘要
基于BP神经网络构建76味补虚药分类模型。采用数据挖掘方法挖掘补虚药药效,利用Python语言实现BP神经网络,并构建药效分类模型及其应用。对12味补虚药进行测试,其中有10味预测结果正确,正确率为83.33%。通过药性分布可知,补虚药的主要特征为温、甘,归经为脾、肾、心经。采用中药性味归经为特征对中药分类进行预测,实验结果表明,基于BP神经网络的药效分类模型具有一定的可靠性和准确性,亦为中药分类方法研究提供了借鉴。
Based on the BP neural network,a classification model of 76 flavored drugs was established. Data mining method was used to mine the efficacy of tonic drugs,and BP neural network was used to construct the pharmacodynamic classification model and its ap-plication. 10 of the 12 flavours were tested correctly with a correct rate of 83.33%. Through the distribution of drug,we can see that the main characteristics of reinforcing deficiency medicine are warm and sweet,and the meridian is the spleen,kidney and heart meridi-an. In this study,the characteristics of flavor meridian of traditional Chinese medicine were used to predict the classification of tradi-tional Chinese medicine. The experimental results show that the classification model based on BP neural network has certain reliability and accuracy,and provides a reference for the study of traditional Chinese medicine classification methods.
作者
刘莉萍
章新友
郭永坤
牛晓录
LIU Li-ping;ZHANG Xin-you;GUO Yong-kun;NIU Xiao-lu(School of Computer,Jiangxi University of Traditional Chinese Medicine,Nanchang 330004,China)
出处
《软件导刊》
2019年第6期6-9,共4页
Software Guide
基金
江西省教育厅科学技术研究项目(GJJ150881)
关键词
中药药性
功效分类
BP神经网络
properties of traditional Chinese medicine
efficacy classification
BP neural network
