The Interval Forecasting Method Based on Non-equidistant GM(1,1) with Application to Regional Grain Production

摘要：

Based on a raw sequence with some aberrant data, it is difficult for any prediction technique to give out an accurate point forecasting value. However, an interval forecasting value obtained by one or more different techniques should be reasonable and acceptable. In this paper, a data sequence having a linear tendency with upper/positive and lower/negative aberrances is analyzed. Upon the linear regression analysis, the data sequence is classified into three parts: upper/positive aberrant data, lower/negative aberrant data and normal data. Then introducing the non-equidistant GM(1,1), we establish three models ： a non-equidistant GM(1,1) based on upper aberrant data, a non-equidistant GM(1,1) based on lower aberrant data and a linear regression model based on the remaining normal data. Using the established models, we can obtain three prediction intervals. Applying it to the prediction of regional grain production, we demonstrate the good performance and effectiveness of the proposed prediction method.

作者: Li Bing-jun He Chun-hua

作者单位: College of Information and Management Science,Henan Agricultural University, Zhengzhou, 450002, China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Grey System and Intelligent Services(2009 IEEE灰色系统与服务科学国际会议)

会议地点: 南京

会议语种:英文

页码: 543-548

在线出版日期: 2009-10-20（万方平台首次上网日期，不代表论文的发表时间）