Based on BP neural network method to establish higher education health evaluation system

Abstract

This paper is here to develop a model that can assess the health status of the higher education system in any country. Then select a country and propose a set of policies that will move that country from its current state to its target state. Five indicators for the evaluation of the education system are formulated. Then, Python crawler is used to capture the data of different countries under these five indicators from the Internet. Then, K-means++ clustering method is used to classify countries into three classes. The significance and specific results of classification are shown in 4.2.1 and Table3. Then, according to different types of countries, TOPSIS based on entropy weight method is used to establish a system that can evaluate the health status of higher education in any country.