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Geomechanics and Engineering Volume 30, Number 3, August10 2022 , pages 247-258 DOI: https://doi.org/10.12989/gae.2022.30.3.247 |
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Study of oversampling algorithms for soil classifications by field velocity resistivity probe |
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Jong-Sub Lee, Junghee Park, Jongchan Kim and Hyung-Koo Yoon
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| Abstract | ||
| A field velocity resistivity probe (FVRP) can measure compressional waves, shear waves and electrical resistivity in boreholes. The objective of this study is to perform the soil classification through a machine learning technique through elastic wave velocity and electrical resistivity measured by FVRP. Field and laboratory tests are performed, and the measured values are used as input variables to classify silt sand, sand, silty clay, and clay-sand mixture layers. The accuracy of k-nearest neighbors (KNN), naive Bayes (NB), random forest (RF), and support vector machine (SVM), selected to perform classification and optimize the hyperparameters, is evaluated. The accuracies are calculated as 0.76, 0.91, 0.94, and 0.88 for KNN, NB, RF, and SVM algorithms, respectively. To increase the amount of data at each soil layer, the synthetic minority oversampling technique (SMOTE) and conditional tabular generative adversarial network (CTGAN) are applied to overcome imbalance in the dataset. The CTGAN provides improved accuracy in the KNN, NB, RF and SVM algorithms. The results demonstrate that the measured values by FVRP can classify soil layers through three kinds of data with machine learning algorithms. | ||
| Key Words | ||
| classification; conditional tabular generative adversarial network (CTGAN); field velocity resistivity probe (FVRP); machine learning; synthetic minority oversampling technique (SMOTE) | ||
| Address | ||
| Jong-Sub Lee, Junghee Park: School of Civil, Environmental and Architectural Engineering, Korea University, 145, Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea Jongchan Kim: Department of Civil and Environmental Engineering, University of California at Berkeley, Berkeley, CA 94720-1710, USA Hyung-Koo Yoon: Department of Construction and Disaster Prevention Engineering, Daejeon University, Daejeon 34520, Republic of Korea | ||