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

查看全文 作　　者：WANG [1]Yuhong;LU [1]Jie

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

出　　处：《Journal of Systems Engineering and Electronics》索引2020年第31卷第3期,共9页

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

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

参考文献(31)

引证文献(18)

耦合文献(159)

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