Applications of improved grey prediction model for power demand forecasting

被引:337
作者
Hsu, CC
Chen, CY
机构
[1] Nan Jeon Jr Inst Technol, Dept Ind Engn & Management, Tainan 73701, Taiwan
[2] Natl Cheng Kung Univ, Inst Resources Engn, Tainan 70101, Taiwan
关键词
grey theory; improved GM(1,1) model; artificial neural network;
D O I
10.1016/S0196-8904(02)00248-0
中图分类号
O414.1 [热力学];
学科分类号
摘要
Grey theory is a truly multidisciplinary and generic theory that deals with systems that are characterized by poor information and/or for which information is lacking. In this paper, an improved grey GM(1,1) model, using a technique that combines residual modification with artificial neural network sign estimation, is proposed. We use power demand forecasting of Taiwan as our case study to test the efficiency and accuracy of the proposed method. According to the experimental results, our proposed new method obviously can improve the prediction accuracy of the original grey model. (C) 2003 Published by Elsevier Science Ltd.
引用
收藏
页码:2241 / 2249
页数:9
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