Soil liquefaction remains an important and interesting problem that has attracted the
development of enumerable prediction models. Increasingly, these models are utilizing …

This research investigates and compares the performance of three tree-based Machine
Learning (ML) methods, Canonical Correlation Forest (CCF), Rotation Forest (RotFor), and …

Seismic soil liquefaction is considered as one of the most complex geotechnical earthquake
engineering problems owing to the uncertainty and complexity involved in soil parameters …

In the present study, an artificial neural network (ANN) model was developed to establish a
correlation between soils initial parameters and the strain energy required to trigger …

Liquefaction-induced lateral spreading has been a very damaging type of ground failure
during past strong earthquakes. Although the occurrence of liquefaction and lateral …

With the rapid development of industry and projects for ensuring the amounts of water that
those industries require, the capacities and scales of hydraulic structures including …

The prediction of lateral spreading is an important task because of the complexities of lateral-
spreading behavior. The aim of this work is to improve an accurate liquefaction-induced …

Liquefaction is one of the most damaging functions of earthquakes in saturated sandy soil.
Therefore, clearly advancing the assessment of this phenomenon is one of the key points for …

Several theoretical and experimental methods are available to estimate pile settlement. Due
to difficulties for obtaining undisturbed samples, many of these methods have been focused …

Abstract Evaluation of liquefaction potential of soils is an important step in many
geotechnical investigations in regions susceptible to earthquake. For this purpose, the use …