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作者:

Li, Hong-Ying (Li, Hong-Ying.) | Chi, Yuan-Ying (Chi, Yuan-Ying.) (学者:迟远英) | Li, Jia-Lin (Li, Jia-Lin.)

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EI Scopus

摘要:

This paper analyzes 38 industrial structures' industry impact factor of China's 31 provinces and cities, with the method of redundancy analysis. The conclusion is as follows: (1) Redundancy analysis is a very potential method of quantitative analysis of the relation between two variables. The redundancy analysis of industry structure has passed statistically significant test, the sort result is good. (2) Currently, the most important factors, which influence the changeable of Chinese industrial structure, are the added value of ten thousand yuan of industrial energy consumption, the staff number, total assets contribution and industrial and mining land. (3) Along with the environmental factor direction, there is a part of the gradient rule in 31 provinces. (4) There is a strong and weak correlation between industries. © 2015 IEEE.

关键词:

Energy utilization Factor analysis Machine learning Redundancy

作者机构:

  • [ 1 ] [Li, Hong-Ying]School of Economics and Management, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Li, Hong-Ying]School of Economics and Management, Hebei University of Science and Technology, Shijiazhuang; 050018, China
  • [ 3 ] [Chi, Yuan-Ying]School of Economics and Management, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Li, Jia-Lin]Beijing-Dublin International College, Beijing University of Technology, Beijing; 100124, China

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来源 :

ISSN: 2160-133X

年份: 2015

卷: 2

页码: 631-636

语种: 英文

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 1

ESI高被引论文在榜: 0 展开所有

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