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Eco-geotechnics for human sustainability
As a result of climate change and increasing engineering activities, soil-related disasters such as slope failures and sandstorms have become more...
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A comprehensive evaluation of ensemble machine learning in geotechnical stability analysis and explainability
We investigated the application of ensemble learning approaches in geotechnical stability analysis and proposed a compound explainable artificial...
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PSO-based Machine Learning Methods for Predicting Ground Surface Displacement Induced by Shallow Underground Excavation Method
Four hybrid intelligent methods are developed to predict the maximum ground surface settlement ( S max ) induced by shallow underground excavation...
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Geotechnics, Heritage, and Sustainability: A Digitized and Transversal Knowledge of the Underground in Architecture Higher Education
This study deals with the work of professors within the area of soil engineering at the University of Seville when teaching architectural content...
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Applying Optimized Machine Learning Models for Predicting Unconfined Compressive Strength in Fine-Grained Soil
This research investigates the potential of optimized machine learning (OML) models for the prediction of UCS in fine-grained soil. Leveraging OML...
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Cross-project prediction for rock mass using shuffled TBM big dataset and knowledge-based machine learning methods
Extensive research has confirmed the successful prediction of rock mass quality in tunnel boring machine (TBM) construction using machine learning...
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Physics Informed Machine Learning (PIML) for Design, Management and Resilience-Development of Urban Infrastructures: A Review
Building resilient and sustainable urban infrastructures is imperative to prepare future generations against new pandemics and climate change...
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Optimization of machine learning models for predicting the compressive strength of fiber-reinforced self-compacting concrete
Fiber-reinforced self-compacting concrete (FRSCC) is a typical construction material, and its compressive strength (CS) is a critical mechanical...
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Unconfined compressive strength prediction of stabilized expansive clay soil using machine learning techniques
This paper evaluates the potential of machine learning techniques, namely, Gaussian Process Regression (GPR) and Support Vector Machine (SVM), for...
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Highly efficient reliability analysis of anisotropic heterogeneous slopes: machine learning-aided Monte Carlo method
Machine learning (ML) algorithms are increasingly used as surrogate models to increase the efficiency of stochastic reliability analyses in...
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Machine learning-based seismic assessment of framed structures with soil-structure interaction
The objective of the current study is to propose an expert system framework based on a supervised machine learning technique (MLT) to predict the...
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A Hybrid Physical and Machine Learning Model for Assessing Landslide Spatial Probability Caused by Raising of Ground Water Table and Earthquake in Atsuma, Japan — Case Study
Landslides are catastrophic natural events primed and/or triggered by extreme rainfalls and strong earthquakes. Simultaneous occurrence of rainfall...
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The Implementation of a Machine-Learning-Based Model Utilizing Meta-heuristic Algorithms for Predicting Pile Bearing Capacity
The main focus in designing pile foundations is the pile bearing capacity (PBC), influenced by various soil characteristics and foundation...
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Identification of Soil Strata from In-Situ Test Data Using Machine Learning
An increasing number of geotechnical analyses such as settlement and stability calculations are performed using 2D or 3D models. In order to obtain a...
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Use of machine learning for classification of sand particles
Particle classification is essential for geotechnical engineering practice since particle shapes correlate with the mechanical and hydraulic...
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Back-calculation of soil parameters from displacement-controlled cavity expansion under geostatic stress by FEM and machine learning
Estimating soil properties from the mechanical reaction to a displacement is a common strategy, used not only in in situ soil characterization (e.g.,...
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Physics-informed deep learning method for predicting tunnelling-induced ground deformations
Tunnelling-induced ground deformations inevitably affect the safety of adjacent infrastructures. Accurate prediction of tunnelling-induced...
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Inverse Design and Application Periodic Barriers for Isolating Ambient Vibration Based on Deep Learning
The vibrations and noises caused by traffic, machine operation, and construction activity have become a serios concern. Fortunately, the use of...
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Evaluation and prediction of slope stability using machine learning approaches
In this paper, the machine learning (ML) model is built for slope stability evaluation and meets the high precision and rapidity requirements in...