摘要
针对经济预测中具有时滞性样本数据序列的预测建模问题,在对GM(1,1)模型拟合残差分析的基础上,结合AR模型及残差自回归模型建立了新的时滞GM(1,1)模型,并给出了该模型一种基于最小二乘的求解算法.最后通过对我国GDP指数进行预测,给出了经济预测中建模的一个应用实例,取得了较为满意的效果.
The paper discusses the modeling problem which has the sample data with a time lag of the sequence in economic forecasting.It bases on the analysis about the fitting residual of GM(1,1) model,adopts AR model to establishes the residual from regression model,and then deduces a new GM(1,1) model,and gives a method which based on the least squares method for solution.At the last,the paper provides a case about the model in the economic forecasts,which is the forecasting about our GDP index.And it achieves a more satisfactory result.
出处
《武汉理工大学学报(交通科学与工程版)》
2011年第5期1067-1071,共5页
Journal of Wuhan University of Technology(Transportation Science & Engineering)
基金
国家自然科学基金项目资助(批准号:70971103)