Enhancing undrained shear strength prediction: a robust hybrid machine learning approach with naïve Bayes modeling
Abstract In geotechnical engineering, it is crucial to make sure that the undrained shear strength (USS) of soft, sensitive clays is accurately assessed. The accuracy in forecasting USS is pivotal for ensuring the structural integrity and stability of foundations and earthworks. Addressing this conc...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-02-01
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| Series: | Journal of Engineering and Applied Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s44147-025-00586-z |
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