title: Optimal Sensor Selection for Classifying a Set of Ginsengs Using Metal-Oxide Sensors.
abstract: The sensor selection problem was investigated for the application of classification of a set of ginsengs using a metal-oxide sensor-based homemade electronic nose with linear discriminant analysis. Samples (315) were measured for nine kinds of ginsengs using 12 sensors. We investigated the classification performances of combinations of 12 sensors for the overall discrimination of combinations of nine ginsengs. The minimum numbers of sensors for discriminating each sample set to obtain an optimal classification performance were defined. The relation of the minimum numbers of sensors with number of samples in the sample set was revealed. The results showed that as the number of samples increased, the average minimum number of sensors increased, while the increment decreased gradually and the average optimal classification rate decreased gradually. Moreover, a new approach of sensor selection was proposed to estimate and compare the effective information capacity of each sensor.
authors.affiliation: State Key Laboratory of Industrial Control Technology, Institute of Cyber Systems and Control, Zhejiang University, Hangzhou 310027, Zhejiang, China. jiacheng@zju.edu.cn.
authors.forename: Jiacheng
authors.initials: J
authors.lastname: Miao
authors.affiliation: State Key Laboratory of Industrial Control Technology, Institute of Cyber Systems and Control, Zhejiang University, Hangzhou 310027, Zhejiang, China. ztlyoyo@163.com.
authors.forename: Tinglin
authors.initials: T
authors.lastname: Zhang
authors.affiliation: State Key Laboratory of Industrial Control Technology, Institute of Cyber Systems and Control, Zhejiang University, Hangzhou 310027, Zhejiang, China. king_wy@zju.edu.cn.
authors.forename: You
authors.initials: Y
authors.lastname: Wang
authors.affiliation: State Key Laboratory of Industrial Control Technology, Institute of Cyber Systems and Control, Zhejiang University, Hangzhou 310027, Zhejiang, China. guangli@zju.edu.cn.
authors.forename: Guang
authors.initials: G
authors.lastname: Li
mesh_terms: D016002:Discriminant Analysis; D062609:Electronic Nose; D004867:Equipment Design; D008670:Metals / Q000737:chemistry*; D009812:Odorants / Q000032:analysis*; D010087:Oxides / Q000737:chemistry*; D005894:Panax / Q000737:chemistry* / Q000145:classification*; D060388:Support Vector Machine
chemical_list: D008670:Metals; D010087:Oxides
keywords: classification; electronic nose; linear discriminant analysis; metal-oxide sensors; sensor selection