Abstract Machine learning (ML) has become the most successful branch of artificial
intelligence (AI). It provides a unique opportunity to make structural engineering more …

Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) are emerging
techniques capable of delivering elegant and affordable solutions which can surpass those …

RC shear walls are commonly used as lateral load-resisting elements in seismic regions,
and the estimation of their shear strengths can become simultaneously design-critical and …

The cementitious matrix of high-performance concrete (HPC) is highly complex, and
ambiguity exists with its mix design. Compressive strength can vary with the composition …

Slope stability prediction plays a significant role in landslide disaster prevention and
mitigation. This study develops an ensemble learning-based method to predict the slope …

This paper presents a practical yet comprehensive implementation of the ensemble methods
for prediction of the shear strength for reinforced concrete deep beams with/without web …

Fault diagnosis of rolling bearing is crucial for safety of large rotating machinery. However, in
practical engineering, the fault modes of rolling bearings are usually compound faults and …

Machine learning techniques are widely used algorithms for predicting the mechanical
properties of concrete. This study is based on the comparison of algorithms between …

Population growth, economic development, and rapid urbanization in many areas have led
to increased exposure and vulnerability of structural and infrastructure systems to hazards …

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