基于改进的向后-向前选择法粗差定位与估值算法
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  • 英文篇名:Algorithm for Location and Evaluation of Gross Errors Based on Improved Backward-Forward Selection Method
  • 作者:柴双武 ; 杨晓琴
  • 英文作者:CHAI Shuangwu;YANG Xiaoqin;College of Mining Technology, Taiyuan University of Technology;
  • 关键词:数据探测法 ; 统计量相关系数 ; 偏相关系数检验 ; 粗差定位 ; 粗差估值
  • 英文关键词:data snooping;;statistical correlation coefficient;;partial correlation coefficient test;;location of gross errors;;evaluation of gross errors
  • 中文刊名:DKXB
  • 英文刊名:Journal of Geodesy and Geodynamics
  • 机构:太原理工大学矿业工程学院;
  • 出版日期:2019-05-15
  • 出版单位:大地测量与地球动力学
  • 年:2019
  • 期:v.39
  • 基金:国家自然科学基金(51504159);; 太原理工大学青年基金(2014TD008)~~
  • 语种:中文;
  • 页:DKXB201905019
  • 页数:6
  • CN:05
  • ISSN:42-1655/P
  • 分类号:102-107
摘要
对传统的向后-向前选择法粗差定位方法进行改进,即在原有基础上加入对平差模型的整体检验,计算统计量的相关系数,通过对偏相关系数的检验来定位统计量相关的粗差观测值。通过模拟粗差算例证明,该算法能够准确定位多维粗差,有效改善粗差定位转移的现象,且粗差估值结果比较可靠。
        In this paper, the traditional backward-forward selection method of gross error locating method is improved: testing the overall adjustment model, calculating the statistic correlation coefficient and using the partial correlation coefficient test are added to locate the statistics related to the gross error observation values. The simulation results show that this algorithm can accurately locate the multidimensional gross errors, effectively improve the gross errors location and transfer, and the estimation results of gross errors are reliable.
引文
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