首页> 美国卫生研究院文献>Journal of Advanced Research >New fast least-squares algorithm for estimating the best-fitting parameters due to simple geometric-structures from gravity anomalies
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New fast least-squares algorithm for estimating the best-fitting parameters due to simple geometric-structures from gravity anomalies

机译:新的快速最小二乘算法用于根据重力异常估算简单几何结构导致的最佳拟合参数

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摘要

A new fast least-squares method is developed to estimate the shape factor (q-parameter) of a buried structure using normalized residual anomalies obtained from gravity data. The problem of shape factor estimation is transformed into a problem of finding a solution of a non-linear equation of the form f(q) = 0 by defining the anomaly value at the origin and at different points on the profile (N-value). Procedures are also formulated to estimate the depth (z-parameter) and the amplitude coefficient (A-parameter) of the buried structure. The method is simple and rapid for estimating parameters that produced gravity anomalies. This technique is used for a class of geometrically simple anomalous bodies, including the semi-infinite vertical cylinder, the infinitely long horizontal cylinder, and the sphere. The technique is tested and verified on theoretical models with and without random errors. It is also successfully applied to real data sets from Senegal and India, and the inverted-parameters are in good agreement with the known actual values.
机译:开发了一种新的快速最小二乘法,可使用从重力数据获得的归一化残余异常来估计掩埋结构的形状因子(q参数)。通过在轮廓的原点和不同点处定义异常值(N值),将形状因子估计的问题转化为寻找形式为f(q)= 0的非线性方程的解的问题。还制定了程序来估计掩埋结构的深度(z参数)和幅度系数(A参数)。该方法简单快速,可以估算产生重力异常的参数。此技术用于一类几何上简单的异常物体,包括半无限垂直圆柱,无限长水平圆柱和球体。该技术在有无随机误差的理论模型上进行了测试和验证。它也已成功应用于塞内加尔和印度的真实数据集,并且反参数与已​​知实际值非常吻合。

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