Attention-based LSTM (AttLSTM) neural network for seismic response modeling of bridges
Y Liao, R Lin, R Zhang, G Wu - Computers & Structures, 2023 - Elsevier
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 …
Seismic response prediction of a train-bridge coupled system based on a LSTM neural network
High complexity and randomness in high-speed train-bridge interactive dynamic analysis
under earthquake lead to massive calculations in high-speed railway seismic design. To …
under earthquake lead to massive calculations in high-speed railway seismic design. To …
LSTM, WaveNet, and 2D CNN for nonlinear time history prediction of seismic responses
Predicting the nonlinear time-history responses of civil engineering structures under seismic
loading remains an essential task in earthquake engineering. This paper explores the …
loading remains an essential task in earthquake engineering. This paper explores the …
Recent advances in uncertainty quantification in structural response characterization and system identification
Structural dynamics has numerous practical applications, such as structural analysis,
vibration control, energy harvesting, system identification, structural safety assessment, and …
vibration control, energy harvesting, system identification, structural safety assessment, and …
Deep learning-based methods in structural reliability analysis: a review
SS Afshari, C Zhao, X Zhuang… - … Science and Technology, 2023 - iopscience.iop.org
One of the most significant and growing research fields in mechanical and civil engineering
is structural reliability analysis (SRA). A reliable and precise SRA usually has to deal with …
is structural reliability analysis (SRA). A reliable and precise SRA usually has to deal with …
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 …
Seismic Reliability Analysis of Structures by an Adaptive Support Vector Regression-Based Metamodel
A Roy, S Chakraborty - Journal of Earthquake Engineering, 2024 - Taylor & Francis
The dual metamodeling approach is usually adopted to tackle the stochastic nature of
earthquakes in seismic reliability analysis relying on the lognormal response assumption …
earthquakes in seismic reliability analysis relying on the lognormal response assumption …
A frequency-based ground motion clustering approach for data-driven surrogate modeling of bridges
Abstract Machine learning–based methods, especially deep learning methods, have
achieved great success in seismic response modeling due to their exceptional performance …
achieved great success in seismic response modeling due to their exceptional performance …
A comparative study of various metamodeling approaches in tunnel reliability analysis
Various metamodeling approaches are applied in conjunction with Monte Carlo simulation
and or the second moment-based method for reliability analyses of underground tunnels …
and or the second moment-based method for reliability analyses of underground tunnels …
Seismic response prediction of RC bridge piers through stacked long short-term memory network
O Yazdanpanah, M Chang, M Park, CY Kim - Structures, 2022 - Elsevier
This paper aims at addressing the prediction of the displacement time histories and
subsequently hysteresis curves of reinforced concrete bridge piers using a real-time hybrid …
subsequently hysteresis curves of reinforced concrete bridge piers using a real-time hybrid …