Apr 10, 2022 · We propose a lithology identification method based on an improved neighborhood rough set and AdaBoost.
Facing the logging data with outliers, unbalance and high complexity, we propose a lithology identification method based on an improved neighborhood rough set ...
Facing the logging data with outliers, unbalance and high complexity, we propose a lithology identification method based on an improved neighborhood rough set ...
Abstract: Traditional lithology identification left the problems of low accuracy, recognition efficiency and generalization ability. Facing the logging data ...
Facing the logging data with outliers, unbalance and high complexity, we propose a lithology identification method based on an improved neighborhood rough set ...
针对测井数据存在异常值、不平衡、复杂度高等特点，提出了一种基于改进邻域粗糙集和AdaBoost的岩性识别方法。在经典邻域粗糙集的基础上，对邻域半径的选取和运行时间进行 ...
J-GLOBAL ID：202202299039087783 Reference number：22A1618397. Lithology identification of logging data based on improved neighborhood rough set and AdaBoost.
We propose logging data representation enhancement approach for lithology identification based on feature decomposition, selection and transformation.
Missing: rough | Show results with:rough
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What type of log do we use for lithology identification?
Facing the logging data with outliers, unbalance and high complexity, we propose a lithology identification method based on an improved neighborhood rough set ...
[PDF] Research on Intelligent Recognition Technology in Lithology ...
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The proposed KPCA-BO-CatBoost model was effective in identifying the formation lithology, realized real-time lithology identification by combining the ...