摘要
结合RBF网络模型和ARIMA模型预测的优点,构建基于RBF网络模型和ARIMA模型的混合模型,对四川省高等教育规模预测问题进行研究。采用构建ARIMA模型得出的预测值对RBF网络模型的预测值进行修正,提高了区域高等教育规模预测的精度。
This paper studies the problem of Sichuan higher education scale forecasting, and establishes the hybrid model based on the advantages of RBF neural network model and ARIMA model. By revising the forecasting value of RBF neural network model through constructing ARIMA model, the efficiency of regional higher education scale forecasting is improved.
出处
《乐山师范学院学报》
2013年第12期6-9,共4页
Journal of Leshan Normal University
基金
四川文理学院校级科研项目(2012Z005Y
2012Z004Z)
关键词
区域高等教育规模
预测
RBF
ARIMA
RBF
ARIMA
Regional Higher Education Scale
Forecasting