Machine learning regression approach for analysis of bearing capacity of conical foundations in heterogenous and anisotropic clays
An upper bound (UB) and lower bound (LB) finite element limit analysis cooperating with a
machine learning method is adopted as a new solution for predicting the bearing capacity of …
machine learning method is adopted as a new solution for predicting the bearing capacity of …
Soft-computing techniques for predicting seismic bearing capacity of strip footings in slopes
In this study, various machine learning algorithms, including the minimax probability
machine regression (MPMR), functional network (FN), convolutional neural network (CNN) …
machine regression (MPMR), functional network (FN), convolutional neural network (CNN) …
[HTML][HTML] Data-driven prediction of stability of rock tunnel heading: an application of machine learning models
In this paper, Artificial Neural Networks (ANN) have been utilized to predict the stability of a
planar tunnel heading in rock mass based on the well-defined Hoek-Brown (HB) yield …
planar tunnel heading in rock mass based on the well-defined Hoek-Brown (HB) yield …
Undrained basal stability of braced circular excavations in anisotropic and non-homogeneous clays
This paper introduces the plastic stability solutions of braced circular excavations in
anisotropic and non–homogeneous clays. Using the framework of Finite Element Limit …
anisotropic and non–homogeneous clays. Using the framework of Finite Element Limit …
End bearing capacity factor for annular foundations embedded in clay considering the effect of the adhesion factor
New limit analysis solutions for the end bearing capacity of annular foundations in clay with
linearly increasing shear strength are presented in the paper. The strength profile of clay …
linearly increasing shear strength are presented in the paper. The strength profile of clay …
Machine learning approaches for prediction of the bearing capacity of ring foundations on rock masses
Determining the bearing capacity of ring foundations on rock masses holds utmost
importance within the framework of foundation design methodology. To examine the failure …
importance within the framework of foundation design methodology. To examine the failure …
A machine learning regression approach for predicting the bearing capacity of a strip footing on rock mass under inclined and eccentric load
In this study, the Multivariate Adaptive Regression Splines (MARS) model is employed to
create a data-driven prediction for the bearing capacity of a strip footing on rock mass …
create a data-driven prediction for the bearing capacity of a strip footing on rock mass …