Improvement and application of GM(1,1) model based on multivariable dynamic optimization
Improvement and application of GM(1,1) model based on multivariable dynamic optimization作者机构:School of BusinessJiangnan UniversityWuxi 214122China
出 版 物:《Journal of Systems Engineering and Electronics》 (系统工程与电子技术(英文版))
年 卷 期:2020年第31卷第3期
页 面:593-601页
核心收录:
学科分类:0711[理学-系统科学] 07[理学] 071101[理学-系统理论]
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)
主 题:grey prediction GM(1,1)model background value grey system theory
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 *** this paper,the Lagrange mean value theorem is used to construct the background value as a variable related to *** 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 *** proves that the improved model is better than any other models.