摘要
针对非等间距灰色系统预测中存在误差较大的问题,结合序列本身的特点和GM(1,1)模型的建模过程,提出了对非等间距序列坡度优化的方法并对其分析,进行局部插值使原模型得到改进,从而提高了模型的拟合和预测精度,拓宽了应用范围。模型中对能源的消费趋势进行预测,找出了能源消费量和GDP之间的内在联系,为科学地分析能源结构提供了依据,对世界稳定、可持续发展有着重要的意义。
To diminish the error in the non-equidistant grey model for forecasting ,considering the characteristic of the sequence,and combining the process of the foundation of GM （1,1）, an approach by using the method of gradient optimizing is presented. It is to operate local interpolation after the optimized analysis, which improves the primary model ,thus,the fitting accuracy and its availability. The model is then used in the prediction of the consume trend of the energy sources and finding the inherent relationship between energy consumption and GDP, providing evidence of scientific analysis of the energy construction, which is very important for the world＇s stability and its sustainable development.
出处
《水电能源科学》
2007年第3期115-118,共4页
Water Resources and Power
关键词
坡度优化
灰色预测
能源消费量
GDP
能源强度
gradient optimiziation
grey prediction energy consumption GDP energy intensity
