Comparison of tree-based machine learning algorithms for predicting liquefaction potential using canonical correlation forest, rotation forest, and random forest based …
This research investigates and compares the performance of three tree-based Machine
Learning (ML) methods, Canonical Correlation Forest (CCF), Rotation Forest (RotFor), and …
Learning (ML) methods, Canonical Correlation Forest (CCF), Rotation Forest (RotFor), and …
Modelling and validation of liquefaction potential index of fine-grained soils using ensemble learning paradigms
This study explores the utilization of ensemble-based soft computing techniques for
predicting the liquefaction potential of fine-grained soils. Generally, deterministic methods …
predicting the liquefaction potential of fine-grained soils. Generally, deterministic methods …
Liquefaction behavior of Indo-Gangetic region using novel metaheuristic optimization algorithms coupled with artificial neural network
The present research aims to co-relate the plasticity and liquefaction response of soil as well
as its significance in defining liquefaction probability. To accomplish this, metaheuristic …
as its significance in defining liquefaction probability. To accomplish this, metaheuristic …
[HTML][HTML] Earthquake-induced liquefaction hazard mapping at national-scale in Australia using deep learning techniques
Australia is a relatively stable continental region but not tectonically inert, having geological
conditions that are susceptible to liquefaction when subjected to earthquake ground motion …
conditions that are susceptible to liquefaction when subjected to earthquake ground motion …
Seismic liquefaction potential assessed by support vector machines approaches
X Xue, X Yang - Bulletin of Engineering Geology and the Environment, 2016 - Springer
Liquefaction of loose, saturated granular soils during earthquakes poses a major hazard in
many regions of the world. Determining the liquefaction potential of soils induced by …
many regions of the world. Determining the liquefaction potential of soils induced by …
Prediction of the single pile seismic deflection by using FEM and ANN
A Namdar, O Mughieda, Y Liu, Y Deyu, Y Dong… - Geotechnical and …, 2024 - Springer
A failure prediction assessment is generally required to enhance infrastructural seismic
design. This study used Artificial Neural Networks (ANN) and the Finite Element Method …
design. This study used Artificial Neural Networks (ANN) and the Finite Element Method …
Seismic liquefaction potential assessed by neural networks
X Xue, E Liu - Environmental Earth Sciences, 2017 - Springer
This study presents two optimization techniques: genetic algorithm (GA) and particle swarm
optimization (PSO), to improve the efficiency of backpropagation (BP) neural network model …
optimization (PSO), to improve the efficiency of backpropagation (BP) neural network model …
Liquefaction study of fine-grained soil using computational model
Liquefaction is one of the most disastrous phenomena that arises due to earthquakes and
has always been a major concern for engineers due to the damages and devastation it …
has always been a major concern for engineers due to the damages and devastation it …
Application of genetic algorithm-based support vector machines for prediction of soil liquefaction
X Xue, M Xiao - Environmental Earth Sciences, 2016 - Springer
This paper presents a hybrid genetic algorithm (GA) and support vector machine (SVM)
techniques to predict the potential of soil liquefaction. GA is employed in selecting the …
techniques to predict the potential of soil liquefaction. GA is employed in selecting the …
Prediction of liquefaction susceptibility of clean sandy soils using artificial intelligence techniques
AS Sabbar, A Chegenizadeh, H Nikraz - Indian Geotechnical Journal, 2019 - Springer
The liquefaction susceptibility of sandy soil is generally characterised by some parameters
in the static liquefaction potential evaluation. These parameters are usually measured by …
in the static liquefaction potential evaluation. These parameters are usually measured by …