文章基本信息

标题：Similarity quantification of soil parametric data and sites using confidence ellipses
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作者：Liang Han ; Lin Wang ; Xuanming Ding 等
期刊名称：Geoscience Frontiers
印刷版ISSN：1674-9871
出版年度：2022
卷号：13
期号：1
页码：1-13
DOI：10.1016/j.gsf.2021.101280
语种：English
出版社：Elsevier
摘要：Graphical abstractDisplay OmittedHighlights•Confidence ellipse is applied to perform parametric data similarity analysis.•Site similarity is analyzed via the proposed mean and weighted mean approaches.•Effects of number and weights of selected parameters are explored.•Correlation models are used to explain the application of similarity analysis.AbstractThis paper presents a confidence ellipse-based method to evaluate the similarity of soil parametric data using the database from the site investigation reports. Then, the obtained similarity assessment results of parametric data are used to further estimate the site similarity via two proposed strategies, namely the mean and weighted mean approaches. The former referred to the average of parametric data similarity degrees, while the latter was the weighted average, and the weight was calculated using the coefficient of variation (COV) of each parameter. For illustration, the liquidity index (LI) dataset was firstly used to explore the performance of the presented method in the evaluation of parametric data similarity. Subsequently, the site similarity was assessed and the effects of numbers and weights of selected parameters for study were systematically studied. Lastly, the transformation models about the relationships betweenCcandωas well as betweenCcande0were constructed to illustrate the application of the similarity analysis in reduction of transformation uncertainty. Results show that the greatest site similarity degree is at about 0.76 in this study, and the maximum decrease of transformation uncertainty can reach up to 18% and 25.5% as union parametric data similarity degree increases. Moreover, the site similarity degree represents the whole similarity between two different sites, and the presented union parameter similarity degree maintains a good agreement with transformation uncertainty.
关键词：KeywordsenSoil parametersSiteConfidence ellipseSimilarity