Sensitivity analysis of ordinary kriging to sampling and positional errors and applications in quality control
Sensitivity analysis of ordinary kriging to sampling and positional errors and applications in quality control
复制标题
DOI：
10.1590/0370-44672015690159
复制
发表时间：
2016-12
期刊：
影响因子：
--
通讯作者：
Victor Miguel Silva;J. Costa
中科院分区：
文献类型：
--
作者：
Victor Miguel Silva;J. Costa
采矿业使用的数据质量控制程序通常根据被视为良好做法的数值或以前适用于类似矿床的数值来界定容限，但估计的精确度和准确度取决于地质特征、估计参数、样本间距和数据质量的组合。本研究探讨样本品质限制如何影响估计结果。拟议的方法是基于一系列衡量标准，用于比较对估计数的影响，使用一个合成数据库，在原始样本等级或位置上增加越来越多的误差，模拟不同的精确度。所提出的方法的结果导致类似于文献中推荐的等级的公差限制。位置不确定性对模型估计值的影响最小，因为当前测量方法的准确性具有毫米量级的偏差，因此其影响可以忽略不计。
Data quality control programs used in the mineral industry normally define tolerance limits based on values considered as good practice or those that have previously been applied to similar deposits, although the precision and accuracy of estimates depend on a combination of geological characteristics, estimation parameters, sample spacing and data quality. This study investigates how the sample quality limits affect the estimates results. The proposed methodology is based on a series of metrics used to compare the impact on the estimates using a synthetic database with an increasing amount of error added to the original sample grades or positions, emulating different levels of precision. The proposed approach results lead to tolerance limits for the grades similar to those recommended in literature. The influence of the positional uncertainty on model estimates is at a minimum, because of the accuracy of current surveying methods that have a deviation in the order of millimeters, so its impact can be considered negligible.