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State of the art in structural health monitoring of offshore and marine structures
This paper deals with state of the art in structural health monitoring (SHM) methods in
offshore and marine structures. Most SHM methods have been developed for onshore …
offshore and marine structures. Most SHM methods have been developed for onshore …
State-of-the-art review on advancements of data mining in structural health monitoring
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 …
statistical methods have been utilized in a remarkable number of structural health monitoring …
Self-supervised learning for electroencephalography
Decades of research have shown machine learning superiority in discovering highly
nonlinear patterns embedded in electroencephalography (EEG) records compared with …
nonlinear patterns embedded in electroencephalography (EEG) records compared with …
Automated structural design of shear wall residential buildings using generative adversarial networks
Artificial intelligence is resha** building design processes to be smarter and automated.
Considering the increasingly wide application of shear wall systems in high-rise buildings …
Considering the increasingly wide application of shear wall systems in high-rise buildings …
Attention-based LSTM (AttLSTM) neural network for seismic response modeling of bridges
Accurate prediction of bridge responses plays an essential role in health monitoring and
safety assessment of bridges subjected to dynamic loads such as earthquakes. To this end …
safety assessment of bridges subjected to dynamic loads such as earthquakes. To this end …
Intelligent structural design of shear wall residence using physics‐enhanced generative adversarial networks
Intelligent structural design using generative adversarial networks (GANs) is a revolutionary
design approach for building structures. Despite its far‐reaching capability, the data quantity …
design approach for building structures. Despite its far‐reaching capability, the data quantity …
Data‐driven rapid damage evaluation for life‐cycle seismic assessment of regional reinforced concrete bridges
Rapid and accurate post‐earthquake damage evaluation of regional reinforced concrete
(RC) bridges is a key issue for assessing the seismic resilience of cities and communities …
(RC) bridges is a key issue for assessing the seismic resilience of cities and communities …
Convolutional neural networks (CNNs)-based multi-category damage detection and recognition of high-speed rail (HSR) reinforced concrete (RC) bridges using test …
The fast networking of high-speed rail (HSR) may cause in-service fatigue and ultimate load
damage to bridges. This paper investigates the application of deep convolutional neural …
damage to bridges. This paper investigates the application of deep convolutional neural …
Image-based reinforced concrete component mechanical damage recognition and structural safety rapid assessment using deep learning with frequency information
Safety assessment of post-event damaged structures is vital and significant because it
directly affects life security, structural repair, and economic loss, especially in earthquakes …
directly affects life security, structural repair, and economic loss, especially in earthquakes …
A deep learning approach to rapid regional post‐event seismic damage assessment using time‐frequency distributions of ground motions
Every year, earthquakes result in severe economic losses and a significant number of
casualties worldwide. In limiting the losses that occur after these extreme events, timely and …
casualties worldwide. In limiting the losses that occur after these extreme events, timely and …