The present study aims to compare the performance of two machine learning techniques
that can unveil the relationship between the input and target variables and predict the …

The prediction of liquefaction-induced lateral spreading/displacement (D h) is a challenging
task for civil/geotechnical engineers. In this study, a new approach is proposed to predict D h …

Backbreak is a rock fracture problem that exceeds the limits of the last row of holes in an
explosion operation. Excessive backbreak increases operational costs and also poses a …

Increasing terrorist attacks towards ordinary or strategic buildings and soft targets represent
one of the major impetus to improve existing methods of design for blast-resistant structures …

Through a tunnel-blasting project, the effect of tunnel-blasting vibration has been analyzed
from the perspective of vibration energy transfer. The non-linear regression method was …

Ground vibration induced by mine blasting is the most significant adverse effect on nearby
residents and surroundings. Accurate prediction of blasting vibration using limited monitor …

Bitumen, aggregate, and air void (VA) are the three primary ingredients of asphalt concrete.
VA changes over time as a function of four factors: traffic loads and repetitions …

Supervised learning by means of Genetic Programming (GP) aims at the evolutionary
synthesis of a model that achieves a balance between approximating the target function on …

This paper introduced a novel Artificial Neural Networks (ANN)-based bond–slip model for
the Near-surface mounted (NSM) FRP system using cement-based adhesives, as an …

The objective of this paper is to present a method for predicting blast-induced ground
vibration in open-pit mines that is based on the use of self-organizing neural networks …