灰色模型GM(1,1)的平滑改进及其应用  

The Smoothing Improvement and the Application of Grey Model GM (1,1)

作　　者：赵晓艳[1] 刘天娇[1] 周波[1] 胡洋[1] 

机构地区：[1]东北电力大学经济管理学院,吉林吉林132012

出　　处：《东北电力大学学报》2006年第4期63-66,共4页Journal of Northeast Electric Power University

摘　　要：灰色预测法能够对含有不确定因素的系统进行预测,而由于整个宏观系统就是一个灰色系统,因此可以考虑用灰色预测模型对宏观经济指标进行预测。在灰色模型GM(1,1)基础上,提出对原始数列进行平滑改进的方法,并用实例证明改进后的灰色模型预测结果比传统灰色模型预测结果误差更小,精度更高。Grey Model can predict a system which contains uncertain factors. As it is known, the whole economic system is grey, so we can predict the economic data with Grey Model. Based on the traditional GM （ 1, 1 ）, this paper puts forward a smoothing improvement method to improve the traditional model It can be. seen from the example that the improved GM （ 1, 1 ） has smaller errors in simulated data and better forecasting precision than the traditional GM （ 1, 1 ）.

关 键 词：灰色模型GM(1 1) 平滑改进 预测精度 

分 类 号：TM715[电气工程—电力系统及自动化]