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基于线性回归的重力数据三维RMS成像
引用本文:吉日嘎拉图,鲁光银.基于线性回归的重力数据三维RMS成像[J].物探化探计算技术,2014(2):185-189.
作者姓名:吉日嘎拉图  鲁光银
作者单位:中南大学地球科学与信息物理学院,长沙410083
基金项目:国家自然科学基金项目(41174061)
摘    要:这里提出了一种基于线性回归的RMS成像方法,通过该方法可以分析判断重力异常源所处位置及赋存范围的方法。经过线性回归,得相关系数、斜率和截距三个参数,利用这三个参数计算RMS并对场源进行成像分析,以得到场源的位置及赋存状况。为了验证算法的可行性,通过简单模型和实测重力异常数据进行试验分析,验证了该方法可以有效地显示出异常地质体的位置及空间赋存状态。

关 键 词:线性回归  相关系数  重力异常  RMS

3-D RMS imaging of gravity data based on linear regression
Ji-ri-ga-la-tu,LU Guang-yin.3-D RMS imaging of gravity data based on linear regression[J].Computing Techniques For Geophysical and Geochemical Exploration,2014(2):185-189.
Authors:Ji-ri-ga-la-tu  LU Guang-yin
Institution:(School of Geosciences and Info Physics, Changsha 410083, China)
Abstract:In this paper, a method based on linear regression analysis to determine the gravity anomaly source location has been developed. By processing the linear regression, we obtain three parameters, such as, correlation coefficient, slope and inter cept. Depending on the above three parameters, we process RMS imaging to analyze the causative body, to obtain its location and occurrence condition. In Order to verify the feasibility and validation of the algorithm; we calculate multiple models and the measured gravity anomaly data. At the meantime, this method determines the abnormal geological bodies, and mode of occur fence especially particularly sensitive to the field source location.
Keywords:linear regression  correlation coefficient  gravity anomalies  RMS
本文献已被 CNKI 维普 等数据库收录!
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