基于模糊C均值聚类的中药材鉴别研究

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【摘   要】   以中药材的中红外光谱数据为聚类分析对象，通过提取影响药材类别的关键特征波数，采用主成分分析结合模糊C均值聚类建立了中药材的鉴别模型。该模型可实现对中药材样本数据的快速鉴别，为中药材鉴别问题的研究提供借鉴。

【关键词】   模糊C均值聚类;主成分分析;中药材鉴别

Identification of Traditional Chinese Medicine Based on

Fuzzy C-Means Clustering

Ding Xueli， Qin Mengjie， Wang Jing

（Fuyang Institute of Technology， Fuyang 236031， China）

【Abstract】    Taking the mid infrared spectrum data of traditional Chinese medicine as the cluster analysis object， the identification model of traditional Chinese medicine was established by extracting the key characteristic wave number affecting the category of traditional Chinese medicine and using principal component analysis combined with fuzzy C-means clustering. This model can not only realize the rapid identification of traditional Chinese medicine sample data， but also provide reference for the research of practical traditional Chinese medicine identification.

【Key words】     fuzzy C-means clustering; principal component analysis; identification of traditional Chinese medicine

〔中图分类号〕  O212               〔文献标识码〕  A              〔文章编号〕 1674 - 3229（2022）02- 0013 - 06

0     引言

我国的中药材资源丰富，种类繁多，品种分布广泛。（剩余3019字）