The Analysis Of Development Situation Of Education Industry In Beijing Based On Improved ARIMA Model

In recent years, as a capital, Beijing has experienced increasingly prominent "big city malaise", when it has being rapidly developed. This is also reflected in the development of the education industry in Beijing, such as education congestion, lack of resources, uneven distribution, etc. Targeting at the problems arising from the development of the education industry in Beijing, the Outline of the Plan for Coordinated Development for the Beijing-Tianjin-Hebei Region (hereinafter referred to as the"Outline")clearly pointed out that the education needed easing as a non-capital core function. At the same time, the Outline also clearly pointed out that non-core functions of Beijing education should be relieved mainly from: strict control of increment and orderly relieving of stock. By establishing a forecasting model for the future growth of educational institutions in Beijing, this paper enables the government to quantitatively analyze the future increment and make more scientific decision-making for controlling increment and easing stock, finally promoting the sustainable development of education in Beijing.In this paper, the above problems are studied, with the main contents as follows:Firstly, from the perspective of information analysis, the information about the development of education in Beijing is collected, collated and analyzed. The present situation and causes of the educational development of Beijing in recent years are analyzed, and the problems arising from the current development process are pointed out.Secondly, among information prediction methods, the improved ARIMA model is used as the prediction model of this paper. This paper introduces the model and its application status, and then uses a hybrid ARIMA and neural network model to predict the changing trend of the number of educational institutions in Beijing and evaluate the prediction results. Because the model can express the linear and nonlinear components in the time series, it has a better prediction effect than the single model, and can more accurately predict the number of educational institutions in Beijing.Thirdly, based on the model prediction results and combining with analysis of the current situation of education in Beijing,this paper provides policy suggestions for how to control and ease the number of educational institutions in Beijing from the perspective of optimizing the allocation of educational resources.