Research of Electronic Nose Pattern Recognition Algorithm Based on SVM

被引：3
|
作者：
Liang, Wei [1 ]
Zhang, Lina [1 ]
Li, Xiaowei [1 ]
Zuo, Yandi [1 ]
机构：
[1] Zhengzhou Univ Light Ind, Zhengzhou 450002, Peoples R China
来源：
ADVANCES IN MANUFACTURING TECHNOLOGY, PTS 1-4 | 2012年 / 220-223卷
关键词：
electronic nose; pattern recognition; support vector;
D O I：
10.4028/www.scientific.net/AMM.220-223.2244
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
In order to improve the recognition rate of the electronic nose system for small samples, an electronic nose pattern recognition algorithm based on support vector machine (SVM) is proposed in this paper. Identification experiments for three kinds of wine with similar odor were carried out. The sensor arrays are optimized by means of principal component analysis (PCA) method first. Then, make comparing experiment using different algorithms for different number of training samples of wine. The related results show that PCA-SVM based pattern recognition algorithms has high recognition accuracy, stronger classification capability, and has potential advantages in small sample classification and recognition experiments.
引用
收藏
页码：2244 / 2247
页数：4
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