Landslide susceptibility map** (LSM) has been widely used as an important reference for
development and construction planning to mitigate the potential social‐eco impact caused …

With the advent of big data era, deep learning (DL) has become an essential research
subject in the field of artificial intelligence (AI). DL algorithms are characterized with powerful …

Industrial solid wastes, such as ultra-fine fly ash (RUFA) and ground granulated blast-
furnace slag (GGBS), hold tremendous potential for recycling due to their abundance and …

It is challenging to develop accurate models for heavy construction equipment residual
value prediction using conventional approaches. This article proposes three Machine …

Accurate prediction of ground vibration caused by blasting has always been a significant
issue in the mining industry. Ground vibration caused by blasting is a harmful phenomenon …

Accurate assessment of undrained shear strength (USS) for soft sensitive clays is a great
concern in geotechnical engineering practice. This study applies novel data-driven extreme …

Geotechnical reliability analysis provides a novel way to rationally take the underlying
geotechnical uncertainties into account and evaluate the stability of geotechnical structures …

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 …

Network intrusion detection system is an essential part of network security research. It
detects intrusion behaviors through active defense technology and takes emergency …

The architecture, engineering and construction (AEC) industry is experiencing a
technological revolution driven by booming digitisation and automation. Advances in …