摘要
为了提高模型的拟合精度,提出了一种新的改进GM(1,1)模型.从优化GM(1,1)模型背景值的定义出发,推导出利用原始数据生成的背景值公式,将其与经过优化的初始条件结合,构造出改进的GM(1,1)模型.此模型将在很大程度上消除由于背景值的选取所产生的误差.对该模型进行数据模拟,通过与原模型中数据的比较、分析,验证出新的优化模型具有更好的模拟精度,说明该模型的有效性,可以将其应用于对其它数据的拟合预测.
In order to optimize the precision in goodness of fit,this paper presents a new improved GM(1,1) model.Based on the definition of background value,the background value function has been derived using original data.Combining with the optimized initial conditions,the improved GM(1,1) model has been constructed.To a great extent,this new GM(1,1) model eliminates the errors generated in the selection of background value.By numerical simulation using the new model,and comparison with the data in original model,it proves that the new model achieves a higher modeling accuracy,which also proves that the new model is efficient and can be used in other data analysis for testing their goodness of fit.
出处
《辽宁工程技术大学学报(自然科学版)》
CAS
北大核心
2012年第2期264-267,共4页
Journal of Liaoning Technical University (Natural Science)
基金
河北省教育厅科研基金资助项目(2009159)