期刊
JOURNAL OF ROCK MECHANICS AND GEOTECHNICAL ENGINEERING
卷 14, 期 4, 页码 1292-1303出版社
SCIENCE PRESS
DOI: 10.1016/j.jrmge.2022.03.002
关键词
Geological characteristics; Stacking classification algorithm (SCA); K-fold cross-validation (K-CV); K-means++
资金
- Pearl River Talent Recruitment Program of Guangdong Province in 2019 [2019CX01G338]
- Research Funding of Shantou University for New Faculty Member [NTF19024-2019]
This study presents a framework for predicting geological characteristics by integrating a stacking classification algorithm (SCA) with a grid search (GS) and K-fold cross validation (K-CV). The accuracy of the SCA can be improved with the use of GS and K-CV. The proposed torque penetration index (TPI) and field penetration index (FPI) express the geological characteristics, while the elbow method (EM) and silhouette coefficient (Si) determine the types of geological characteristics.
This study presents a framework for predicting geological characteristics based on integrating a stacking classification algorithm (SCA) with a grid search (GS) and K-fold cross validation (K-CV). The SCA includes two learner layers: a primary learner's layer and meta-classifier layer. The accuracy of the SCA can be improved by using the GS and K-CV. The GS was developed to match the hyper-parameters and optimise complicated problems. The K-CV is commonly applied to changing the validation set in a training set. In general, a GS is usually combined with K-CV to produce a corresponding evaluation index and select the best hyper-parameters. The torque penetration index (TPI) and field penetration index (FPI) are proposed based on shield parameters to express the geological characteristics. The elbow method (EM) and silhouette coefficient (Si) are employed to determine the types of geological characteristics (K) in a K-means++ algorithm. A case study on mixed ground in Guangzhou is adopted to validate the applicability of the developed model. The results show that with the developed framework, the four selected parameters, i.e. thrust, advance rate, cutterhead rotation speed and cutterhead torque, can be used to effectively predict the corresponding geological characteristics. (C) 2022 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Production and hosting by Elsevier B.V.
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