摘要
DGM(1,1)模型对近似齐次指数增长序列具有较高的预测精度,而实际上服从近似齐次指数增长规律的数据序列十分有限。根据灰色系统理论的差异信息原理,通过原始序列的累减生成将近似非齐次指数增长序列转化为近似齐次指数增长序列,对累减生成序列建立DGM(1,1)模型,并在此基础上实现对原始序列的还原以达到数据模拟及预测之目的。因原始序列的累减生成最大可能地满足了建模序列的齐次性要求,提高了模拟及预测精度,拓展了模型的适用范围,故通过算例验证了此种改进方法的简单性、实用性及有效性。
The precision,with applying the DGM（1,1）model to forecast a homogeneous exponential incremental sequence,is satisfactory;however,incremental sequences which are approximate to meet the homogeneous exponential distribution are very limited.According the principle of informational differences in grey system theory,a non-homogeneous exponential incremental sequence may be converted into a homogeneous one through inverse accumulating generator of a raw sequence,next,a model of DGM（1,1） is built by the new sequence,and then,after reverting to the original sequence,it can accomplish the targets of simulation and prediction for the raw sequence.An indirect DGM（1,1）model,with approximately meeting the homogeneity demand of a modeling sequence by the greatest possible degree,improves the precision of simulation and prediction,extends the range of application of the raw DGM.Ultimately,two examples show the simplicity,practicability and validity of the improved approach.
出处
《统计与信息论坛》
CSSCI
2010年第8期30-33,共4页
Journal of Statistics and Information
基金
国家自然科学基金项目<具有灰色不确定信息特征的GM拓展预测模型及其应用研究>(70701017)
教育部博士点基金项目<基于GTRS仿真网络的非常规突发事件情景推演与测算问题研究>(90924022)
关键词
灰色系统理论
预测模型
间接DGM(1
1)模型
非齐次指数增长序列
累减生成
grey system theory
prediction model
indirect DGM（1
1）model
non-homogeneous exponential incremental sequence
inverse accumulating generator
