NDLI: Similarity evaluation of cigarette aroma components based on kernel principal component analysis

Content Provider	IEEE Xplore Digital Library
Author	Li Junli Yin Gengyun Mao Jianlin Duan Shaomi
Copyright Year	2013
Description	Author affiliation: Coll. of Inf. Eng. & Autom., Kunming Univ. of Sci. & Technol., Kunming, China (Li Junli; Mao Jianlin; Duan Shaomi) \|\| Yunnan Acad. of Tobacco Sci., Kunming, China (Yin Gengyun)
Abstract	The type and content of aroma components are the main factors affecting the tobacco style. For tobacco production enterprises, the style analysis is very important to compare their own products with the competitors. Principal component analysis method based on kernel function is a nonlinear multivariate statistical analysis method with favorable effect in dimensionality reduction. In this paper, the high-dimensional data up to 63 index of tobacco aroma compositions were mapped into two-dimensional feature space by kernel principal component analysis, and the information amount of feature data is not less than 95%. Inter-class dispersion was introduced to evaluate the aroma components similarity of nine brands products. The results showed that the evaluation of nine brands cigarette based on the proposed method was consistent with the Chinese cigarette style feature classification and brand market segmentation. Such method can provide effective theoretical support for the traditional classification method of cigarette-style feature.
Starting Page	8348
Ending Page	8352
File Size	130196
Page Count	5
File Format	PDF
ISBN	9789881563835
ISSN	19341768
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	TCCT, CAA
Subject Keyword	Feature extraction polynomial kernel function Eigenvalues and eigenfunctions Inter-class dispersion Mathematical model Kernel aroma components kernel principal component analysis Dispersion Equations Principal component analysis
Content Type	Text
Resource Type	Article

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