标题：The Application of Improved GM(1,1) in Power Load Forecasting
作者：Fan Chengxian; Shi Kaiquan; Kejun Li
作者机构：[Fan Chengxian; Kejun Li] Shandong Univ, Sch Elect Engn, Jinan 250100, Peoples R China.; [Shi Kaiquan] Shandong Univ, Sch Math & Syst Sci, Jinan, Pe 更多
会议名称：International Conference on Advanced Measurement and Test (AMT 2010)
会议日期：MAY 15-16, 2010
来源：PROGRESS IN MEASUREMENT AND TESTING, PTS 1 AND 2
关键词：Improved GM(1,1); Gray related degree; Revised parameter; Logarithm; Smoothing
摘要：The forecasting precision of GM(1,1) is very low, when the data sequence is not smooth. The logarithm smoothing is used for the original data sequence. Considering the low precision caused by overlarge vertical bar a vertical bar and forecasting gray interval for gray modeling, A novel method is proposed for power load forecasting: weighted forecasting method of gray related degree with revised parameter and logarithm smoothing. The method can make various factors weaken or counteracted and prevent the forecasting data from too fast increasing. The proposed model is demonstrated by a test in a certain area. The result shows that the method is effective both in theory and in practice.