Abstract
This paper presents a discussion of “Applying Knowledge-Guided Machine Learning to Slope Stability Prediction” by Te Pei, Tong Qiu, and Chaopeng Shen. https://doi.org/10.1061/JGGEFK.GTENG-11053.
Data-driven approaches work best with big data. However, geotechnical case histories are often limited, thereby restricting the application of data-driven approaches. The authors addressed this problem by generating additional data using domain knowledge–based models, and tested this concept with the slope stability problem. The paper is interesting and will serve as a useful reference on this topic.
This discussion provides valuable insights and highlights several errors in the database used by the authors. In addition, potential limitations of the knowledge-based models used in the paper are also discussed.
Data-driven approaches work best with big data. However, geotechnical case histories are often limited, thereby restricting the application of data-driven approaches. The authors addressed this problem by generating additional data using domain knowledge–based models, and tested this concept with the slope stability problem. The paper is interesting and will serve as a useful reference on this topic.
This discussion provides valuable insights and highlights several errors in the database used by the authors. In addition, potential limitations of the knowledge-based models used in the paper are also discussed.
Original language | English |
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Journal | Journal of Geotechnical and Geoenvironmental Engineering |
Volume | 150 |
Issue number | 9 |
Early online date | 15 Jul 2024 |
DOIs | |
Publication status | Published - 1 Sept 2024 |