Machine learning (ML) has evolved rapidly over recent years with the promise to
substantially alter and enhance the role of data science in a variety of disciplines. Compared …

Several probabilistic liquefaction triggering approaches, or liquefaction manifestation
severity approaches, have been developed to consider the uncertainties related to …

Among the research hotspots in geological/geotechnical engineering, research on the
prediction of soil liquefaction potential is still limited. In this research, several machine …

The electric cone penetration test (CPT) has been in use for over 40 years and is growing in
popularity in North America. This paper provides some recent updates on the interpretation …

Soil liquefaction has been accepted as one of the factors causing natural disasters and
engineering failures in the seismic. The mathematic prediction model for soil liquefaction is …

Observations from recent earthquakes and the results of cyclic tests indicate that the
Chinese criteria are not reliable for determining the liquefaction susceptibility of fine-grained …

This paper presents a complete methodology for both probabilistic and deterministic
assessment of seismic soil liquefaction triggering potential based on the cone penetration …

Prediction of liquefaction potential of any soil deposit is itself a very challenging task. The
problem becomes even more demanding when it becomes necessary to incorporate the …

This paper presents a new evolutionary neural network (ENN) algorithm coupled with the
dimensionality reduction technique 't-distributed stochastic neighbour embedding'(t-SNE) …

A series of monotonic and cyclic triaxial shearing tests on Toyoura sand are simulated by
discrete element method (DEM) incorporating rolling resistance. The input parameters are …