摘要
GM(1,1)模型的白化解为齐次指数形式,而一般数据呈非齐次指数形式,存在形式上的差异.本文运用非齐次级比与非齐次指数函数的对应关系,对原始序列中相邻数据做差处理,得到新的序列,将非齐次指数序列转换为齐次指数序列,再建立GM(1,1)模型.实例表明,运用初值优化和非齐次化能提高GM(1,1)模型的精度.
The form of whitening solution of while that of general data is non-homogeneous GM（1, 1） model is homogeneous exponential exponential, there are differences in two forms In this paper, we firstly apply the corresponding relationship between the non-homogeneous class ratio and non-homogeneous exponential function, and do difference processing to the original sequence adjacent data to get a new sequence, which change the non-homogeneous exponential sequence to a homogeneous one, then establish a GM（1, 1） model.The application example shows that the fit precision of the initial value modify model and non-homogeneous grey model can be enhanced.
出处
《数学的实践与认识》
CSCD
北大核心
2014年第22期309-314,共6页
Mathematics in Practice and Theory
基金
高等学校博士学科点专项科研基金(20120143110001)
教育发展社科基金(11YJC630155)
湖北省青年基金(Q20121203)
平顶山学院中青年骨干教师培养资助项目(20128024)
关键词
GM(1
1)模型
平移变换
函数变换
非齐次级比
单调序列
GM（1, 1） model
translation transformation
function transformation
non-homogeneous class ratio
