摘要
目的采用模糊C均值聚类(FCM)和硬C均值聚类(HCM)算法对蒙医方剂进行类别划分,探讨2种聚类算法的合理性。方法选取《传统蒙药与方剂》中治疗赫依病的27首蒙医方剂,进行数据预处理。采用MS Visual Studio 2010平台,使用C#语言进行开发,分别运用Window From、WPF技术实现汉、蒙文版本。采用FCM和HCM算法按3、4、5、6个类对数据进行聚类分析。结果所有相异数不为零的分类都存在包含现象,2种聚类算法得到的分类结果中药物不存在交叉。与HCM算法比较,FCM算法的分类结果中各类样本数量差较小,即分类较均匀。结论 2种算法均正确合理,其中FCM算法具有更好的聚类效果,可广泛应用于蒙医方剂分析,为新药研制提供数据支持。
Objective To classify Mongolian medicine prescription by using fuzzy c-means algorithm(FCM)and hard c-means algorithm(HCM);To explore the rationality of two kinds of clustering algorithm.Methods27Mongolian medicine prescriptions for treating Heiyi disease from Chuan Tong Meng Yao Yu Fang Ji were set as experimental data,and the data were preprocessed first.MS Visual Studio2010platform was used,and C#language was used for research and development.Chinese version and Mogolian version were implemented with WindowFrom and WPF technology,respectively.The medicine prescriptions were classified into3,4,5,and6types by using FCM and HCM.Results All categorization with zero classification showed the existence of inclusion phenomena.The medicine in the classification results obtained by the two kinds of clustering algorithm did not exist cross.FCM could produce clustering results with smaller quantity difference and the more uniform classification compared with HCM.Conclusion The two algorithms are correct and reasonable,in which FCM algorithm has better clustering effect,and can be widely used in Mongolian prescription analysis,with a purpose to provide data supports for the research and development of new medicine.
作者
张春生
包.图雅
李艳
ZHANG Chun-sheng;BAO Tu-ya;LI Yan(College of Computer Science and Technology, Inner Mongolia University for Nationalities, Tongliao 028043, China)
出处
《中国中医药信息杂志》
CAS
CSCD
2017年第8期99-103,共5页
Chinese Journal of Information on Traditional Chinese Medicine
基金
国家自然科学基金(81460656)
关键词
模糊C均值聚类
硬C均值聚类
蒙医
方剂
聚类
配伍
fuzzy c-means algorithm
hard c-means algorithm
Mongolian medicine
prescription
clustering
compatibility
