摘要
由于传统GM(1,1)模型白化方程为常系数微分方程,因而在原始数据呈指数增长且变化速度快的情况下不适用。为此,论文提出了2种拓展的灰色GM(1,1)模型,针对灰色作用量b进行白化方程修正并给出了建模方法,最后以苏州市GDP为例进行实例分析。结果表明,论文给出的拓展灰色模型对高增长时间序列有较好的适应性,能较为有效地对其进行拟合与预测。
As the whitening equation of the traditional GM(1,1)model is a constant coefficient differential equation,it is not applicable when the original data grow exponentially and change quickly.Therefore,this paper proposes two extended grey GM(1,1)models by modifying the grey action b in the differential equation of GM(1,1)and gives their modeling methods separately.Finally,we carried on a case study of Suzhou GDP.The results show that the extended grey models presented in this paper have good adaptability to high growth time series and that they can fit and predict it effectively.
作者
刘昀
程毛林
LIU Yun;CHENG Maolin(School of Mathematical Sciences,SUST,Suzhou 215009,China)
出处
《苏州科技大学学报（自然科学版）》
2022年第2期15-21,44,共8页
Journal of Suzhou University of Science and Technology（Natural Science Edition）
基金
国家自然科学基金资助项目(11401418)。
