NDLI: The research on the comprehensive evaluation of Herbal Medicine industry development using nonlinear principal component analysis and cluster analysis

Content Provider	IEEE Xplore Digital Library
Author	Wenjun Xie
Copyright Year	2012
Description	Author affiliation: Institution of Systems Engineering of Huazhong University of Science and Technology, 430074, Wuhan, China (Wenjun Xie)
Abstract	China is the largest country to produce and consume Chinese medicine in world. People have come to realize that the side effects of chemical medicine gradually because serious pollution, ecological environment deterioration and human ‘lifestyle disease’ are among the most severe challenges with which human beings are faced today. The voice for “return to nature” becomes louder and louder. To find effective natural medicine instead of chemical medicine has become the development trend of the international medicine. So we use nonlinear principal component analysis and cluster analysis to evaluate comprehensively of Herbal Medicine industry development, and to give the improved method of non-dimensional quantities data and processing non-linear data, and to establish a new comprehensive evaluation method to analyze nonlinear principal component and cluster on the base of ‘logarithm center method’. Then it is proved the influence of Herbal Medicine industry development on Factors of the per capital GDP, the total output value of Herbal Medicine industry, the total retail amount of healthy consumption, the total volume of trade of Herbal Medicine wholesale retail and freight transportation.
Starting Page	546
Ending Page	549
File Size	615539
Page Count	4
File Format	PDF
ISBN	9781457703430
e-ISBN	9781457703454
DOI	10.1109/ICIST.2012.6221706
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-03-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Industries Humans Cities and towns Covariance matrix Indexes Principal component analysis Logistics
Content Type	Text
Resource Type	Article

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