基于垂直距离最小二乘拟合的双曲线沉降模型

Hyperbolic Settlement Model Based on Least squares Orthogonal Distances Fitting

  • 摘要: 引入临时坐标系,采用高斯 牛顿迭代算法,在双曲线基于垂直距离最小二乘拟合算法的基础上增加一个角度约束条件和两个平移约束条件,对沉降数据进行双曲线几何拟合而非代数拟合,提出了一种基于垂直距离最小二乘拟合的双曲线沉降模型的曲线参数估计算法。算例表明,改进算法改善了传统算法的拟合精度。

     

    Abstract: By adopting a temporary coordinate system and adding one angular constraint and two translation constraints on the base of hyperbolic’s least squares orthogonal distances fitting algorithm, a hyperbolic settlement model based on least squares orthogonal distances fitting was put forward in this paper, in order to fit the settlement data to a hyperbolic using geometric fitting algorithm rather than algebraic fitting algorithm. The results of an example show that the advanced algorithm has a better accuracy by comparison of the traditional fitting algorithm.

     

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