摘要
针对序列增长趋势不完全满足准指数规律时的灰色预测建模问题,提出基于GM(1,1)模型与序列增长趋势之间偏差修正的建模方法,将GM(1,1)模型还原式中的常数项作为灰变量处理,加入调整系数以缩小拟合值与实际值之间的增长趋势差异,利用灰色离散模型拟合调整系数的变化过程,将得到的调整系数拟合值带入原时间响应函数,进而得到趋势修正的原始序列拟合值;运用新的建模方法对南京市第三产业用电量进行拟合和预测,证明了方法有效提升了GM(1,1)建模精度,并且拟合序列和实际序列的灰色绝对关联度得到提高.
For the problem of modeling the sequence not meeting completely the quasi exponential law, this paper puts forwards a new method of correcting the difference of changing trends between the original sequence and the model by revising coefficients; the constant in the restoring formation is transformed to a grey variable, and an adjust coefficient is used to reduce the difference between the fitting sequence and the original sequence, then use the discrete grey model to simulate the coefficient sequence, with which the fitting value is acquired from the revised time response function; the application predicts the electricity power consumption of Nanjing＇s tertiary industry , and the improved the accuracy of GM（1,1） model fitting sequence and the original sequence result shows that the new modeling method has as well as the absolute degree of grey incidence of has been improved.
出处
《数学的实践与认识》
CSCD
北大核心
2014年第22期55-59,共5页
Mathematics in Practice and Theory
基金
国家自然科学基金(71071077
71371098)
中央高校基本科研业务费专项资金(NC2012001NR2013015)
高校哲学社会科学重点研究基地重大项目(2012JDXM005)
关键词
灰色预测
趋势修正模型
常数变异
拟合精度
grey prediction
trend correction model
constant variation
simulation precision
