With the extensive adoption of artificial intelligence (AI), construction engineering and
management (CEM) is experiencing a rapid digital transformation. Since AI-based solutions …

To date, data mining (DM) techniques, ie artificial intelligence, machine learning, and
statistical methods have been utilized in a remarkable number of structural health monitoring …

A novel semi-active control algorithm for adaptive variable stiffness intelligent structures that
combines the fuzzy control strategy with Long Short-Term Memory (LSTM) is proposed in …

Recent breakthroughs in computing power have made it feasible to use machine learning
and deep learning to advance scientific computing in many fields, including fluid mechanics …

Advancements in computing power have recently made it possible to utilize machine
learning and deep learning to push scientific computing forward in a range of disciplines …

Photographs of bridges can reveal considerable technical information such as the part of the
structure that is damaged and the type of damage. Maintenance and inspection engineers …

This study proposes a novel self‐training framework for unsupervised domain adaptation in
the segmentation of concrete wall cracks using accumulated crack data. The proposed …

Regular detection of defects in drainage pipelines is crucial. However, some problems
associated with pipeline defect detection, such as data scarcity and defect counting difficulty …

Predicting the nonlinear time-history responses of civil engineering structures under seismic
loading remains an essential task in earthquake engineering. This paper explores the …

Effective post‐earthquake response requires a prompt and accurate assessment of
earthquake‐induced damage. However, existing damage assessment methods cannot …