Analysis of China Railway Passenger Volume's Influence Factors Based on Principal Component Regression

被引:0
|
作者
Gu, Song [1 ]
Lu, Xiaochun [1 ]
机构
[1] Beijing Jiaotong Univ, Sch Econ & Management, Beijing 100044, Peoples R China
关键词
railway passenger volume; factor analysis; principal component regression; analysis of influence factors;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Now the speed of the development of railway passenger transport market has exceeded the freight's, the proportion of passenger transport's income is constantly increasing in the total income, which makes it significant to find a simple and reliable method to analyze the factors that affect China railway passenger transport market. On the basis of relevant study, using the principal component regression theory, which can solve collinearity problems, this paper establish a multiple linear regression model, which has strong practical significance. Moreover, this paper studies how do related variables influence the change of railway passenger volume and the degrees of these influences quantificational.
引用
收藏
页数:5
相关论文
共 50 条
  • [31] Application of Hierarchical Clustering Based on Principal Component Analysis to Railway Station Classification
    Xu, Chang'an
    Li, Junjie
    Zou, Congcong
    Ni, Shaoquan
    PROCEEDINGS OF THE SIXTH INTERNATIONAL CONFERENCE ON TRANSPORTATION ENGINEERING (ICTE 2019), 2019, : 162 - 171
  • [32] POLAROGRAPHIC ANALYSIS OF PYRAZINES BY PRINCIPAL COMPONENT REGRESSION
    Yong Nian NI Department of Chemistry
    Mark Selby and Mark Hodgkinson School of Chemistry
    Chinese Chemical Letters, 1992, (09) : 721 - 722
  • [33] Application of Principal Component Regression Analysis in Economic Analysis
    Chen Ming-ming
    Ma Jing-lian
    PROCEEDINGS OF THE 2015 3RD INTERNATIONAL CONFERENCE ON MANAGEMENT SCIENCE, EDUCATION TECHNOLOGY, ARTS, SOCIAL SCIENCE AND ECONOMICS (MSETASSE 2015), 2015, 41 : 1205 - 1208
  • [34] RESEARCH ON FACTORS INFLUENCING THE TEAMWORK ON RAILWAY PASSENGER TRAIN IN CHINA
    Tao Yuchun
    Qiu Lei
    SECOND INTERNATIONAL SYMPOSIUM ON INNOVATION & SUSTAINABILITY OF MODERN RAILWAY - PROCEEDINGS OF ISMR '2010, 2010, : 436 - 441
  • [35] Corrected Principal Component Regression and Its Application in China's Urban Employment Demand
    Zhang, Ying-ying
    OuYang, Jing-yi
    PROCEEDINGS OF THE 3D INTERNATIONAL CONFERENCE ON APPLIED SOCIAL SCIENCE RESEARCH, 2016, 105 : 788 - 791
  • [36] Applying Principal Component Analysis and Grey Relation Analysis to Analyze the Influence Factors of Quality and Safety of Dairy Products in China
    Li, Dafang
    Wu, Qingchun
    PROCEEDINGS OF 2017 IEEE INTERNATIONAL CONFERENCE ON GREY SYSTEMS AND INTELLIGENT SERVICES (GSIS), 2017, : 58 - 63
  • [37] Passenger Service Improvement in China's High Speed Railway Passenger Stations
    Xia, Shengli
    Liu, Fang
    INNOVATION AND SUSTAINABILITY OF MODERN RAILWAY, 2012, : 810 - +
  • [38] THE BEST CHOICE OF COTTON SUBSIDY MODES BASED ON PRINCIPAL COMPONENT REGRESSION IN XINJIANG, CHINA
    Wang, Xiaoyin
    Tan, Yanwen
    Li, Yuhong
    INTELLIGENT DECISION MAKING SYSTEMS, VOL. 2, 2010, : 544 - 549
  • [39] Railway passenger traffic volume prediction based on neural network
    Wang Zhuo
    Jia Li-Min
    Qin Yong
    Wang Yan-Hui
    APPLIED ARTIFICIAL INTELLIGENCE, 2007, 21 (01) : 1 - 10
  • [40] Improved support vector regression and its application to prediction of railway passenger traffic volume
    Xia, Guoen
    Jin, Weidong
    Zhang, Gexiang
    Xinan Jiaotong Daxue Xuebao/Journal of Southwest Jiaotong University, 2007, 42 (04): : 494 - 498