正权重组合预测模型及其在经济中的应用  

Combined Model for Forecasting Based on Positive Weight and Its Application in the Economy

作　　者：沈存根[1,2] 周开君[2] 王宏华[3] 

机构地区：[1]河海大学商学院,南京2190098 [2]中共国家税务总局党校,江苏扬州225007 [3]河海大学电气学院,南京210098

出　　处：《经济数学》2010年第1期85-91,共7页Journal of Quantitative Economics

摘　　要：介绍了组合预测的方法,并利用最优组合和递归方差倒数方法对组合预测方法进行改进;提出通过GMDH方法首先对影响经济预测模型的各变量进行筛选然后再建立回归模型、神经网络模型等单项预测模型的思想;最后结合GMDH方法建立的时间序列模型,建立正权重组合预测模型.The combined forecasting and the way of improving such forecasting methodology through optimized combination and recursion were introduced. The GMDH was proposed to be applied to select variables relevant to economic forecasting models before establishing a single forecasting model such as regression model and neural network model. And the final step was to establish a combined model for forecasting based on positive weight by using the time series model, which was established according to the GMDH.

关 键 词：正权重 组合预测 GMDH 神经网络 

分 类 号：O211.67[理学—概率论与数理统计]