Abstract
Typical geotechnical testing results reflect the level of soil uncertainty, which requires statistical corrections of the data for an appropriate engineering decision. This study proposes frameworks to detect outlying data points using statistical analyses, the cross-validation-based method and the generalised extreme value distribution-based method. The borehole data regarding soil depth distribution in a central area of Seoul, South Korea are assessed to validate the aforementioned methods for comparison with the distribution-based method and the Moran scatterplot method. The results show that the proposed methods enable more reliable spatial distributions to be achieved with a quantitative evaluation of local reliability.
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