Predicting on Scale Development of Higher Education Based on LM and ANN

The paper employs Granger causality test to analyze the inner relationships among factors that attribute to the scale development of higher education, and builds an Artificial Neural Network (ANN) and a Logistic Model (LM) to forecast the total demand and supply of the scale development of higher education in the process of urbanization in Jiangxi province. The results show: Firstly, the Granger causality test reveals that the key parameters that impact the scale development of higher education are the per capita GDP and the urbanization rate. Secondly, the elasticity analysis of demand to supply of the scale development of higher education reveals the development of higher education in Jiangxi province is entering the stage with E<1 when the critical point E>1 passed after 1999. Therefore, its development of higher education should be paid more attention to the quality, and the scale that is quickly expanding should be appropriately controlled.