Grey prediction with rolling mechanism for electricity demand forecasting of Shanghai

被引：0

作者：

Wang, Xiping ^{[1
]}

机构：

[1] N China Elect Power Univ, Sch Business Adm, Baoding 071003, Peoples R China

来源：

PROCEEDINGS OF 2007 IEEE INTERNATIONAL CONFERENCE ON GREY SYSTEMS AND INTELLIGENT SERVICES, VOLS 1 AND 2 | 2007年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The traditional Grey model has been widely used in various forecasting systems, including electricity demand forecasting. However, it is reported that the accuracy of the model is not satisfactory. In this paper, Grey prediction with rolling mechanism (GPRM) approach is proposed to predict the total and industrial electricity consumption of Shanghai. GPRM is used because of high prediction accuracy, applicability in the case of limited data situations and requirement for little computational effort. Results show that the forecasting precision of GPRM for total and industrial electricity demand is improved. And future projections have also been done for total and industrial sector, respectively.

引用

页码：689 / 692

页数：4

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