摘要
传统的灰色预测模型所需的样本容量较少,仅4个数据就可以建立灰色预测模型。虽然传统的灰预测建模较为简单,但是忽略了对预测较为有利的新信息,容易产生预测模型老化的现象,预测精度不高。全信息新陈代谢的GM(1,1)灰色预测模型更为合理、科学,全信息建模避免了局部信息建模的局限性,每预测一个结果去除原始数列的最老数据的新陈代谢处理保证了预测数列的实效性,并用Matlab实现改进GM(1,1)模型的编程计算,应用于双流县电力需求量的预测,预测精度好。
It＇ s easy to establish gray forecasting model with only four sample data by traditional gray method, but the ＂latest information was neglected, which resulted in obsolescence model of low precision. The improved GM （ 1,1 ） of gray forecasting model was more rational and scientific. Limitations was avoided when modeling with all information. When a new data was forecasted,the oldest data was removed, which ensured the effectiveness of the data. The improved GM （ 1,1 ） model calculation program was achieved by Matlab. It turned out well dealing with the electric load prediction in Shuangliu county.
出处
《计算机技术与发展》
2012年第1期9-12,共4页
Computer Technology and Development
基金
中国水利水电科学研究院开放基金项目(08SL-01)
水资源与水电工程科学国家重点实验室(2008B040)
双流县"十二五"规划课题研究
关键词
全信息
新陈代谢
电力预测
MATLAB
all information
metabolism
electric demand forecasting
Matlab
