基于最小二乘支持向量机的普通高校招生人数预测研究

Application of Least Squares Support Vector Machine for Forecast of Regular Higher Learning Institution Enrollment

近年来普通高校的发展速度与规模,使社会大众兴起了对教育质量与总量的关注。普通高校招生数预测是制定教育政策的重要依据。针对中国文化教育的特征,在统计学习理论和结构风险最小化原理的基础上,建立了基于最小二乘支持向量机的时间序列预测模型。预测结果表明该模型具有较高的预测精度,为普通高校招生数预测提供了一条新的途径。

In recent years the scale and the rate of growth in college, caused the community pay close attention to education quality and the total quantity. The forecast of regular higher learning institution enrollment is an important resource for establish educational policy. In view of China culture and education characteristic, the least squares support vector machine prediction model is given based on the principle of the statistical learning theory and structural risk minimization. The result is given that the forecasting model is effective and offers a new method to forecast the regular higher learning institution enrollment.