作　　者： (孙浩）; (杨桂元）;

机构地区： 安徽财经大学统计与应用数学学院,安徽蚌埠233030

出　　处： 《齐齐哈尔大学学报（自然科学版）》 2017年第6期86-91,共6页

摘　　要： 以2006~2015年的我国小麦最低收购价作为研究对象,运用灰色预测、多元线性回归以及二次指数平滑法三种单项预测方法预测在不同时点上的我国小麦最低收购价,在使用广义诱导有序加权对数平均算子(GIOWLA算子)的基础上,引入Theil不等系数,构建了基于Theil不等系数的GIOWLA算子的最优组合预测模型,并对模型进行有效性检验。检验结果表明,该组合预测模型优于传统的单项预测模型,能够充分利用各个单项预测方法的信息并能提高预测精度,是一种优性组合预测,故用此组合预测模型预测了2016~2020年我国小麦最低收购价,使得预测结果更加合理有效。 Based on the minimum purchase price of wheat in China from 2006 to 2015,three kinds of single forecasting methods,gray prediction,multiple linear regression and quadratic exponential smoothing method,were used to predict the minimum purchase price of wheat in China at different time points. On the basis of the orderly weighted logarithmic mean operator （GIOWLA operator）,the optimal combination forecasting model of GIOWLA operator based on a proximity degree is constructed and the validity of the model is tested. The results show that the proposed model is superior to the traditional single prediction model,and can make full use of the information of each individual forecasting method and improve the prediction accuracy. It is a kind of combination forecast. Therefore, this combination forecasting model predicts 2016 -2020 China＇s minimum purchase price of wheat,making the forecast results more reasonable and effective.

关 键 词： 不等系数 算子 优性组合预测