An improved algorithm of the spatial coordination analysis on higher education resources and employment population

Tianjin University of Technology and Education, Luban Workshop International Development Research Center, 300222 Tianjin, China

^* Corresponding author: lei@tute.edu.cn

Abstract

The traditional evaluation criteria of coordination analysis were based on the classification of fixed interval index. Clustering methods serve to redefine the criteria and improve the accuracy of the coordination analysis. The improved algorithm was adopted to analyze the spatial coordination between Chinese higher educational institutions and employment population. It was discovered:1.The regional imbalance of the higher educational institutions was less serious than that of the employment population;2.Although the coordination level of developing regions in the south-central and north-east was lower than that of western border and eastern coastal regions, all those regions globally maintained a high level of coupling and coordination; 3. Inclusive regional development strategies could be adopted to optimize the coordination between education and employment.