中国农业科学院农业信息研究所 中国农学会
Agricultural Information Institute of CAAS China Association of Agricultural Science Societies
En
Ch
中国农业科学院农业信息研究所 中国农学会 主办

AI检索

订阅

返回顶部
当前位置: 首页 > 文章 > Fisher线性判别法在干酪分类鉴别中的应用 食品科学 2008,29 (6) 41-44
Position: Home > Articles > Application of Fisher Linear Discriminant Method in Cheese Flavors Differentiation FOOD SCIENCE 2008,29 (6) 41-44

Fisher线性判别法在干酪分类鉴别中的应用

作  者：
贾宗艳;田立军;郑丽敏;朱虹;芦筱菲;任发政
单  位：
中国农业大学信息与电气工程学院
关键词：
干酪;电子鼻;Fisher;模式识别
摘  要：
基于气敏传感器阵列和模式识别技术,本研究提出了一种依据干酪的气味对干酪进行分类的方法。对国内光明、三元、台湾Anchor、法国百吉福、欧洲多美鲜5种不同品牌的奶酪气味进行了采样,并从每个传感器的响应曲线上提取了6个特征值。对利用主成分分析的方法对特征向量进行了降维,并建立了特征库。利用Fisher线性判别法建立了区分干酪的两种线性分类器,并重新采样对两种分类器进行了测试比较,其中一种方法的识别的正确率仅为50%,另一种达到了100%。
译  名：
Application of Fisher Linear Discriminant Method in Cheese Flavors Differentiation
作  者：
JIA Zong-yan,TIAN Li-jun,ZHENG Li-min,ZHU Hong,LU Xiao-fei,REN Fa-zheng (College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China)
关键词：
cheese;electronic nose;Fisher;pattern recognition
摘  要：
Based on the sensory array and pattern recognition, a new method to differentiate the cheese by their different flavors was put forward. Five brands of different cheese flavors,such as Guangming, Sanyuan, Anchor, Pikifou and Suki, were sampled,and six features on the response curve filtered of every gas sensor were picked up. There were thirty features for every sample. And then the features were extracted with the principal component analysis (PCA). The feature database was built up. Two linear classifiers were established with Fisher Linear Discriminant Method. Being tested, the accuracy of discrimination with one method is 50%, and that of another one is 100%.

相似文章

导出引用
计量
文章访问数: 11
HTML全文浏览量: 0
PDF下载量: 0

所属期刊

推荐期刊

友情链接Friendly link
农业信息研究所Agricultural information institute 农业智能知识服务平台Agricultural intelligent knowledge service platform 农业学术服务平台Agricultural Knowledge Service System 中国知网CNKI 维普网VIP 万方WANFANG DATA
联系我们Contact us

电话Tell：010-82109652-808

邮箱E-mail：agrijournal@caas.cn

服务Service
关于我们About us 意见建议Opinions and suggest
版权说明Copyright
单位：中国农业科学院农业信息研究所 中国农学会 © 2017中国农业科学院农业信息研究所 ICP备案号：京ICP备09089781号-46