Prediction of skirted foundation safety factors under combined loading in spatially variable soils using machine learning
Authors:
- 1 October 2025
- journal article
- research article
- Published by Springer Nature in Frontiers of Structural and Civil Engineering
- Vol. 19 (10) , 1719-1738
Abstract
No abstract availableKeywords
This publication has 51 references indexed in Scilit:
- Numerical study of the bearing capacity of the hybrid skirted foundations in silty sand under combined loadingApplied Ocean Research, 2024
- Bearing capacity of monopile-bucket composite foundation in sand-over-clay under V-H-M combined static loadsApplied Ocean Research, 2024
- Probabilistic slope stability analysis considering the non-stationary and spatially variable permeability under rainfall infiltration-redistributionBulletin of Engineering Geology and the Environment, 2023
- Slope stability analysis based on big data and convolutional neural networkFrontiers of Structural and Civil Engineering, 2022
- Effects of installation on combined bearing capacity of a spudcan foundation in spatially variable clayApplied Ocean Research, 2022
- Machine Learning Techniques to Predict Rock Strength ParametersRock Mechanics and Rock Engineering, 2022
- Interaction behavior and load sharing pattern of piled raft using nonlinear regression and LM algorithm-based artificial neural networkFrontiers of Structural and Civil Engineering, 2021
- Prediction of shield tunneling-induced ground settlement using machine learning techniquesFrontiers of Structural and Civil Engineering, 2019
- Dynamic prediction for attitude and position in shield tunneling: A deep learning methodAutomation in Construction, 2019
- Evaluation of undrained failure envelopes of caisson foundations under combined loadingApplied Ocean Research, 2016