Abstract
An order parameter selection algorithm based on correlation analysis and principal component analysis was designed according to the statistical analysis method, the selection principle of order parameters of social system, and the correlation test in correlation analysis and the variable contribution test in principal component analysis in this paper. The redundant variables were eliminated from the system by correlation analysis first, and then the variables with high contribution to the system were selected by principal component analysis, so the order parameters obtained accordingly not only have low information redundancy, but also reflect the actual information of the social system to the greatest extent. At the end of this paper, the logistics sector in Gansu Province was taken as an example to select the panel data from 2006 to 2015. Eight indices were extracted as the order parameters of the logistics sector in Gansu Province from the sixteen indices which are redundant selected by this algorithm. The order parameters selected by rational judgment reflect 99% of the original information. The results show that the order parameters in the social system can be correctly and reasonably selected by this order parameter selection algorithm based on correlation analysis and principal component analysis.
Highlights
Each phase of the system development experiences the transformation between quantitative change and qualitative change to different extent
Different from the previous order parameter selection methods, an order parameter selection algorithm based on correlation analysis and principal component analysis was designed from a new perspective on the selection of order parameters mainly according to the statistical analysis method and selforganization theory in this paper
Based on the above problems, an order parameter selection algorithm based on correlation analysis and principal component analysis is designed in such an idea that on the basis of the redundant variable set selected from the system, the correlation analysis of the variables is carried out and the redundant variables in the selected redundant variable set are eliminated first to ensure the simplicity; the principal component analysis of the remaining variables is carried out and the variables with high contribution to the system are selected by the factor load in order to obtain the order parameter of the system
Summary
Each phase of the system development experiences the transformation between quantitative change and qualitative change to different extent. In the field of natural science, the order parameters are usually identified by using the experimental method for repeated phase transformation of the system based on the characteristics of the system itself This method is often impractical and difficult to achieve in the field of social science. Different from the previous order parameter selection methods, an order parameter selection algorithm based on correlation analysis and principal component analysis was designed from a new perspective on the selection of order parameters mainly according to the statistical analysis method and selforganization theory in this paper. The reasonable and objective order parameters can be selected for various social systems by this algorithm
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