基于模糊C均值算法的云南草药聚类分析  

Clustering analysis of Yunnan traditional drug based on fuzzy C-means algorithm

作　　者：黄超[1] 何晋[1] 

机构地区：[1]云南民族大学电气信息工程学院,昆明650500

出　　处：《计算机应用》2012年第A02期32-33,81,共3页journal of Computer Applications

基　　金：国家自然科学基金资助项目(6116361/F020809)

摘　　要：针对云南草药识别方法的简单性、不科学性问题,提出一种基于模糊C均值算法的聚类方法。利用高效液相色谱法提取云南特色草药肉桂的指纹图谱,再通过模糊C均值算法对指纹图谱数据进行聚类。通过与传统K均值算法进行对比,实验结果证明模糊C均值算法具有较高的分类识别能力。Concerning the simplicity and unscientificity of Yunnan traditional drug＇s identification method, a kind of clustering method based on fuzzy C-means algorithm was proposed in this paper. Using high performance liquid chromatography, the fingerprint from Yunnan characteristic drug cinnamon was extracted, and then the data of fingerprint was clustered by the fuzzy C-means algorithm. In comparison with the traditional K-means algorithm, the experiment results show that fuzzy C-means algorithm has higher classification and recognition ability.

关 键 词：云南草药 指纹图谱 聚类分析 模糊C均值算法 K均值算法 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]