Improvement and application of GM(1,1) model based on multivariable dynamic optimization  

作　　者：WANG Yuhong LU Jie 

机构地区：[1]School of Business,Jiangnan University,Wuxi 214122,China

出　　处：《Journal of Systems Engineering and Electronics》2020年第3期593-601,共9页系统工程与电子技术（英文版）

基　　金：supported by the National Natural Science Foundation of China (71871106);the Blue and Green Project in Jiangsu Province;the Six Talent Peaks Project in Jiangsu Province (2016-JY-011)

摘　　要：For the classical GM(1,1)model,the prediction accuracy is not high,and the optimization of the initial and background values is one-sided.In this paper,the Lagrange mean value theorem is used to construct the background value as a variable related to k.At the same time,the initial value is set as a variable,and the corresponding optimal parameter and the time response formula are determined according to the minimum value of mean relative error(MRE).Combined with the domestic natural gas annual consumption data,the classical model and the improved GM(1,1)model are applied to the calculation and error comparison respectively.It proves that the improved model is better than any other models.

关 键 词：grey prediction GM(1 1)model background value grey system theory 

分 类 号：N941.5[自然科学总论—系统科学]