基于Simpson公式的GM(1,N)建模的新算法  

New algorithm for GM(1,N) modeling based on Simpson formula

作　　者：何满喜[1] 王勤[1] 

机构地区：[1]中国计量学院数学系,杭州310018

出　　处：《系统工程理论与实践》2013年第1期199-202,共4页Systems Engineering-Theory & Practice

基　　金：国家自然科学基金(10601051);浙江省自然科学基金(Y6090472)

摘　　要：根据时间序列的结构与特征,对GM(1,N)灰微分方程进行了建模机理分析,并用数值积分算法提出了基于Simpson公式的建立GM(1,N)预测模型的新算法.用平均相对误差对一些时间序列进行了模型的实证分析,发现新算法的拟合精度比原有算法有明显的改进,从而验证了该算法对一些时间序列的有效性.所提出的新算法是建立GM(1,N)预测模型时值得尝试的一个方法,对GM(1,N)预测模型的合理应用具有一定的现实意义.This paper mainly deals with the analysis on mechanism modeling of GM（1,N） grey differential equations, based on the structure and characteristics of time series. By the numerical integration method a new algorithm of GM（],N） forecasting model based on Simpson formula is proposed. Using the method of average relative error, we take empirical anMysis on some time series models, and then find that the new algorithm has more accurate fitting precision than the original one. And the validity of the new algorithm is verified for some time series. The new algorithm is worth to be tried on establishing GM（1,N） forecasting model. And the reasonable application of GM（I,N） forecasting model has a practical significance.

关 键 词：SIMPSON公式 GM(1 N)预测模型 拟合精度 新算法 

分 类 号：N941.5[自然科学总论—系统科学]