摘要
GM(1,1)预测模型一直是灰色系统理论研究者关注的热点。在已有灰色理论的基础上,利用“最小二乘法”确定GM(1,1)白化函数的时间响应函数中的常数C,摈弃了传统GM(1,1)把原始序列中X(0)(1)作为初始条件的做法,从而构建了GM(1,1)的优化模型。最后,以河南省农村劳动力转移预测为例,进行两类预测模型的模拟精度比较,并进行了预测。表1,参7。
The GM （ 1, 1 ）, as s kind of forecasting model to applied widely, is the most important content or the core of grey system theory. Based on the present theories, we utilize the method of “the least square estimate” to discover the constant number c in the Time Reponse Sequence of whiterization equation of GM （ 1, 1 ） after find the development coefficient and grey action quantity, and we abandon themodus operandi to regard X^（0） （1）, the first number of raw sequence, as the initial value of the whiterization equation of GM （1, 1） because we think it be unscientific. Then. establish the optimum time rseponse sequence of whiterization equation for GM （ 1, 1 ）. Then, we forecast the diversion of rual labors of He＇ nan province with the optimal GM （ 1, 1 ） and make a precision comparison between the traditional, GM （1, 1 ） and the optimal one.
出处
《农业系统科学与综合研究》
CSCD
2005年第3期175-177,共3页
System Sciemces and Comprehensive Studies In Agriculture
基金
国家自然科学基金项目(70473037)豫教育厅人文社科基金项目(2004-QN-008).
关键词
GM(1
1)模型
时间响应函数
最小二乘法
农村劳动力
GM （1,1） model
time response sequence
the least square estimate
forecasting
rural labors
