期刊文献+

AR模型的整体最小二乘解算及其应用 被引量:2

Total least-squares based on AR model and its applications
原文传递
导出
摘要 AR模型在变形监测及其预报中应用广泛,因为系数矩阵和预测值都存在误差,宜采用整体最小二乘法。本文通过一个实例对该方法进行验证,计算结果表明,该方法获得的预测值更加接近实测值,并且比传统的方法更具优势,有较强的理论研究价值和实用价值。 AR model is widely used in deformation monitoring and forecasting, because the coefficient matrix and predictive value both exist errors, the total least-squares should be adopted. In the paper, it used an example to verify this method, and the results showed that the predictive value was much closer to the measured values, and had more advantages than the traditional method. It would have a strong theoretical study and practical value.
出处 《测绘科学》 CSCD 北大核心 2013年第2期171-172,167,共3页 Science of Surveying and Mapping
关键词 AR模型 变形监测 整体最小二乘 参数 AR model deformation monitoring total least-squares parameter
  • 相关文献

参考文献5

二级参考文献20

  • 1陈永奇 吴子安 等.变形监测分析与预报[M].北京:测绘出版社,1997..
  • 2Golub G H,van Loan C F. An Analysis of the Total Least Squares Problem[J]. SIAM Journal on Numerical Analysis, 1980,17(6) :883-893.
  • 3Sehaffrin B. A Note on Constrained Total Least- Squares Estimation[J]. Linear Algebra and Its Applications,2006,417 : 245-258.
  • 4Schaffrin B, Wieser A. On Weighted Total Leastsquares Adjustment for Linear Regression[J]. J Geod,2008, 82:415-421.
  • 5邱卫宁.测量数据理论与方法[M].武汉:武汉大学出版社,2008.
  • 6Golub G H, Lan Loan F C. An Analysis of the Total Least Squares Problem[J]. SIAM Journal on Numerical Analysis, 1980,17(6 ) : 883-893.
  • 7Schaffrin B, Felus Y A. On the Multivariate Total Least-squares Approach to Empirical Coordinate Transformations [J].Three Algorithms J Geod, 2008,82:373-383.
  • 8Schaffrin B, Felus A Y. Multivariate Total Least- squares Adjustment for Empirical Affine Transformations[C]. The 6th Hotine Marussi Symposium for Theoretical and Computational Geodesy, Springer, Berlin, 2007.
  • 9Schaffrin B, Lee I P, Felus Y A, et al. Total Least-squares (TLS) for Geodetic Straight-line and Plane Adjustment[J]. Boll Geod Sci Affini, 2006, 65(3): 141-168.
  • 10Schaffrin B. A Note on Constrained Total Leastsquares Estimation[J]. Linear Algebra Appl, 2006, 417(1) :245-258.

共引文献144

同被引文献15

  • 1王朋辉,范胜林,刘建业.GPS/SINS超紧组合导航的性能分析[J].导航与控制,2010,9(2):1-6.
  • 2DEYSTJ J,DECKERTI C. Maximum Likelihood Failure Detection Techniques Applied to the Shuttle RCSJet [J]. Journal of Spacecraft and Rockets, 1976,13(2):65-74.
  • 3ISERMANN R. Process Fault Detection Based on Modeling and Estimation Methods A Survey [J]. Automatica, 1984,20 (4) : 387-404.
  • 4WILSON E. Experiments in Neural Network Control of a Free-flying Space Robot [D]. Stanford:Stanford University, 1995.
  • 5PATTON R J,FRANK P M,CLARK R N. Issues of Fault Diagnosis for Dynamic System [M]. Berlin:Springer Verlag, 2000.
  • 6DA R, LIN C F. Failure Detection of Dynamical Systems with the State Chi-square Test[J].Journal of Guidance, Control and Dynamics, 1994,17 (2) : 271-277.
  • 7DA R,LINCF. Sensitivity Analysis Algorithm for the State Chi-squareTest [J]. Journal of Guidance.Control and Dynamics, 1996,19( 1 ) : 219-222.
  • 8李春科.改进的状态X2故障检验方法及其应用[D].西安:西北工业大学,2008.
  • 9郑加柱,郭斐.变形监测数据的时间序列分析[J].森林工程,2008,24(4):50-53. 被引量:14
  • 10杨知,任鹏,党耀国.反向累加生成与灰色GOM(1,1)模型的优化[J].系统工程理论与实践,2009,29(8):160-164. 被引量:40

引证文献2

二级引证文献19

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部