Research on Evaluation Algorithm of the Higher Education System Based on Neural Network

Abstract

The evaluation of a country’s higher education system is an academic subject of great research value, which helps to explore the defects of the national higher education system, so as to promote the healthy development of the higher education system. In this paper, we collect health data on higher education in many countries, including gross enrollment rate, percentage of higher education expenditure in government education, ratio of unemployed people to total unemployment at higher education level, graduation rate, entry employment rate, teacher-student ratio, Legatum Prosperity Index (education). After that, we take the top six indicators of various countries as input and Legatum Education Prosperity Index as output and establish a neural network comprehensive evaluation model to measure the health level of higher education in various countries. Through the empirical analysis of the model applied to the actual data of six countries, it is found that the health level of higher education in El Salvador is relatively low.