Pre‐and post‐earthquake regional loss assessment using deep learning
As urban systems become more highly sophisticated and interdependent, their vulnerability
to earthquake events exhibits a significant level of uncertainties. Thus, community‐level …
to earthquake events exhibits a significant level of uncertainties. Thus, community‐level …
Deep neural network‐based regional seismic loss assessment considering correlation between EDP residuals of building structures
Regional seismic loss assessment is essential for developing an emergency response plan
in the event of an earthquake, which can reduce casualties and socioeconomic losses in an …
in the event of an earthquake, which can reduce casualties and socioeconomic losses in an …
[HTML][HTML] Probabilistic evaluation of seismic responses using deep learning method
Structural failures caused by a strong earthquake may induce a large number of casualties
and huge socioeconomic losses. To design a structure that can withstand such earthquake …
and huge socioeconomic losses. To design a structure that can withstand such earthquake …
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 …
Efficient regional seismic risk assessment via deep generative learning of surrogate models
Efficient regional seismic risk assessment including ground motion prediction and damage
risk estimation is needed for emergency response planning. However, a conventional …
risk estimation is needed for emergency response planning. However, a conventional …
Attention mechanism based neural networks for structural post-earthquake damage state prediction and rapid fragility analysis
This paper is devoted to the research on applying the deep learning method to nonlinear
structural post-disaster damage state assessment. Transformer and Informer networks with a …
structural post-disaster damage state assessment. Transformer and Informer networks with a …
Evaluation of deep learning models for building damage mapping in emergency response settings
Integrated with remote sensing technology, deep learning has been increasingly used for
rapid damage assessment. Despite reportedly having high accuracy, the approach requires …
rapid damage assessment. Despite reportedly having high accuracy, the approach requires …
Transfer learning for improving seismic building damage assessment
The rapid assessment of building damage in earthquake-stricken areas is of paramount
importance for emergency response. The development of remote sensing technology has …
importance for emergency response. The development of remote sensing technology has …
Fast seismic response estimation of tall pier bridges based on deep learning techniques
C Li, H Li, X Chen - Engineering Structures, 2022 - Elsevier
Seismic responses of tall pier bridges are usually estimated with nonlinear time history
analysis (NLTHA) since it is able to provide rigorous results while the time consumption is …
analysis (NLTHA) since it is able to provide rigorous results while the time consumption is …
Near-real-time identification of seismic damage using unsupervised deep neural network
Prompt identification of structural damage is essential for effective postdisaster responses.
To this end, this paper proposes a deep neural network (DNN)–based framework to identify …
To this end, this paper proposes a deep neural network (DNN)–based framework to identify …