Within seismology, geology, civil and structural engineering, deep learning (DL), especially
via generative adversarial networks (GANs), represents an innovative, engaging, and …

Earthquake Disaster Assessment (EDA) plays a critical role in earthquake disaster
prevention, evacuation, and rescue efforts. Deep learning (DL), which boasts advantages in …

Abstract Machine learning (ML) has emerged as a powerful tool for prediction of systems
behavior in many engineering disciplines. A few applications of ML techniques are available …

Long-span cable-stayed bridges are prone to significant vibrations under strong wind events
such as typhoons, which pose a risk to the bridge functioning and the driving safety of …

Vertical-component of ground motions (GM) plays a significant role in seismic hazard
analysis, especially for long-span structures and high-rising buildings. The former is usually …

In this paper, an integrated framework based on conditional adversarial neural network
(cGAN) is established to simulate ground motions for earthquake scenarios with different …

Cumulative absolute velocity (CAV) is a powerful intensity measure for quantifying potential
earthquake damage to structures. Machine learning (ML) methods can provide more …

In the current study, ground motion models (GMMs) are derived using the European Strong
Motion (ESM) database for pseudo‐spectral acceleration (PSA), peak ground acceleration …

Compressive membrane/arch action at small deformations and resistance evolution path at
large deformations are two key factors in determining whether an RC frame structure can …

In long-span suspension bridges, premature failure of bearings or expansion joints has
been a concern during the bridge service life. To implement a reasonable inspection …