Artificial intelligence in the AEC industry: Scientometric analysis and visualization of research activities
Abstract The Architecture, Engineering and Construction (AEC) industry is fraught with
complex and difficult problems. Artificial intelligence (AI) represents a powerful tool to assist …
complex and difficult problems. Artificial intelligence (AI) represents a powerful tool to assist …
[HTML][HTML] Machine learning in construction: From shallow to deep learning
The development of artificial intelligence technology is currently bringing about new
opportunities in construction. Machine learning is a major area of interest within the field of …
opportunities in construction. Machine learning is a major area of interest within the field of …
Interpretable XGBoost-SHAP machine-learning model for shear strength prediction of squat RC walls
DC Feng, WJ Wang, S Mangalathu… - Journal of Structural …, 2021 - ascelibrary.org
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 …
and the estimation of their shear strengths can become simultaneously design-critical and …
[HTML][HTML] Automatic crack classification and segmentation on masonry surfaces using convolutional neural networks and transfer learning
Masonry structures represent the highest proportion of building stock worldwide. Currently,
the structural condition of such structures is predominantly manually inspected which is a …
the structural condition of such structures is predominantly manually inspected which is a …
Failure mode and effects analysis of RC members based on machine-learning-based SHapley Additive exPlanations (SHAP) approach
Abstract Machine learning approaches can establish the complex and non-linear
relationship among input and response variables for the seismic damage assessment of …
relationship among input and response variables for the seismic damage assessment of …
Vision transformer-based autonomous crack detection on asphalt and concrete surfaces
Previous research has shown the high accuracy of convolutional neural networks (CNNs) in
asphalt and concrete crack detection in controlled conditions. Yet, human-like generalisation …
asphalt and concrete crack detection in controlled conditions. Yet, human-like generalisation …
[PDF][PDF] A review on deep learning-based structural health monitoring of civil infrastructures
XW Ye, T Jin, CB Yun - Smart Struct. Syst, 2019 - researchgate.net
In the past two decades, structural health monitoring (SHM) systems have been widely
installed on various civil infrastructures for the tracking of the state of their structural health …
installed on various civil infrastructures for the tracking of the state of their structural health …
[HTML][HTML] Deep learning for manufacturing sustainability: Models, applications in Industry 4.0 and implications
Recent advancements and developments in artificial intelligence (AI) based approaches
have shifted the manufacturing practices towards the fourth industrial revolution, considered …
have shifted the manufacturing practices towards the fourth industrial revolution, considered …
[HTML][HTML] Methodological-technological framework for construction 4.0
F Muñoz-La Rivera, J Mora-Serrano, I Valero… - … methods in engineering, 2021 - Springer
The construction industry has traditionally been characterised by the high diversity of its
agents and processes, high resistance to change and low incorporation of technology …
agents and processes, high resistance to change and low incorporation of technology …
Classification and analysis of deep learning applications in construction: A systematic literature review
R Khallaf, M Khallaf - Automation in construction, 2021 - Elsevier
In recent years, the construction industry has experienced an expansion in the multitude of
projects and emergent information. With the advent of deep learning, new opportunities …
projects and emergent information. With the advent of deep learning, new opportunities …