Research on Evaluation Model of System Optimization Using Statistical Metrology and Coefficient Variation Method

With the rapid development of society, the healthy and sustainable higher education system is particularly important. As the level of higher education varies in different countries, it is therefore necessary to assess the health of the higher education system comprehensively, in order to make up for its deficiencies. The aim of this contribution is to establish a series of models for assessment, as well as put forward specific policy recommendations to help improve the education index of designated countries or regions. In this work, we collect plenty of data related to higher education. Based on Principal Component Analysis (PCA), we select 20 second-level indicators out of 36 initial indicators. Then, we divide these 20 indicators into 5 groups and construct a three-level evaluation index system to get Higher Education Evaluation Index (HEEI). Next, we determined weight of each indicator using both the Entropy Weight Method (EWM) and Coefficient Variation Method (CVM). And then we set three levels for the HEEI through K-means algorithm to establish the Higher Education Evaluation Model.