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 …

While artificial intelligence (AI), and by extension machine learning (ML), continues to be
adopted in parallel engineering disciplines, the integration of AI/ML into the structural …

Forecasting building fire development and critical fire events in real-time is of great
significance for firefighting and rescue operations. This work proposes an artificial …

The identification of building fire evolution in real-time is of great significance for firefighting,
evacuation, and rescue. This work proposed a novel framework of Artificial-Intelligence …

Abstract Machine learning (ML) continues to rise as an effective and affordable method of
tackling engineering problems. Unlike other disciplines, the integration of ML into structural …

A major fire disaster is hazardous to both occupants trapped in the built environment and
firefighters during the firefighting operation. Though various construction codes …

Automatic real-time fire characterization is a crucial requirement of future smart firefighting.
This work proposes a novel computer vision method to automatically measure the fire heat …

The performance-based design (PBD) has been widely adopted for building fire safety over
the last three decades, but it requires a laborious and costly process of design and approval …

Abstract Machine learning algorithms have emerged as an effective and popular decision-
making tool for solving complicated engineering problems and challenges. Although …