• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>Grey Systems and Intelligent Services, 2009. GSIS 2009 >An improved algorithm of grey model-GM(1,1) based on total least squares and its application in deformation forecast
【24h】

An improved algorithm of grey model-GM(1,1) based on total least squares and its application in deformation forecast

机译：基于总最小二乘的灰色模型-GM（1,1）改进算法及其在变形预测中的应用

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper presents an improved algorithm for grey model-GM(1,1) based on total least squares (TLS). As we know that the parameters a and b in grey model-GM(1,1) can be solved by the least squares method. The LS method is based on an assumption that vector Y contains errors while repeated additive matrix B is accurate in GM(1,1). When we analyze the element of matrix B, the matrix B also contains errors in fact. TLS is the method of fitting that is appropriate when there are errors in both vector Y and matrix B. The calculated results of an example show that the prediction model based on TLS can enhance the prediction accuracy.
机译：本文提出了一种基于总最小二乘（TLS）的灰色模型GM（1,1）的改进算法。我们知道，灰色模型-GM（1,1）中的参数a和b可以通过最小二乘法求解。 LS方法基于以下假设：向量Y包含错误，而重复的加法矩阵B在GM（1,1）中是准确的。当我们分析矩阵B的元素时，矩阵B实际上也包含错误。 TLS是当向量Y和矩阵B都存在错误时的适合方法。实例计算结果表明，基于TLS的预测模型可以提高预测精度。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号