Journal of Systems Engineering and Electronics ›› 2009, Vol. 31 ›› Issue (2): 471-474.

• 软件、算法与仿真 • 上一篇    下一篇

估计GM(1,1)模型参数的一种新方法

刘威1, 崔高锋2   

  1. 1. 中国飞行试验研究院, 陕西, 西安, 710089;
    2. 中国人民解放军96626部队, 福建, 泉州, 362100
  • 收稿日期:2007-10-20 修回日期:2008-04-16 出版日期:2009-02-20 发布日期:2010-01-03
  • 作者简介:刘威(1982- ),女,助理工程师,硕士,主要研究方向为应用数学,灰色系统理论与应用.E-mail:wei182@126.com

New method for the estimation of GM(1,1) parameters

LIU Wei1, CUI Gao-feng2   

  1. 1. Chinese Flight Test Establishment, Xi'an 710089, China;
    2. No.96626 Unit. of PLA, Quanzhou 362100, China
  • Received:2007-10-20 Revised:2008-04-16 Online:2009-02-20 Published:2010-01-03

摘要: 考虑到最小二乘法则的不足及背景值参数和边值的影响,提出基于最小一乘准则估计GM(1,1)模型参数,得到新的预测公式,引入粒子群算法直接求解最小一乘问题即可得到模型参数,简化了以往改进模型的二次求解过程.数值计算结果表明,基于粒子群算法及最小一乘准则估计灰色模型参数,对于平稳或非平稳序列,都具有较高的拟合与预测精度.

Abstract: Considering the disadvantage of the least square criteria and the influence of background value parameter and boundary improvement condition to model prediction accuracy,the least absolute criteria is offered to estimate the parameters of GM(1,1),and the new grey prediction formula is proposed.The parameters are obtained by particle swarm optimization in one step,predigesting the usual process based on the two steps method.The Analysis of some examples indicates that the new method improves the precision of fitting and forecasting of the model for stable or unstable data sequence.

中图分类号: