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Seismic intensity estimation for earthquake early warning using optimized machine learning model
The need for an earthquake early-warning system (EEWS) is unavoidable to save lives. In
terms of managing earthquake disasters and achieving effective risk mitigation, the quick …
terms of managing earthquake disasters and achieving effective risk mitigation, the quick …
Real-time seismic intensity measurements prediction for earthquake early warning: A systematic literature review
Z Cheng, C Peng, M Chen - Sensors, 2023 - mdpi.com
With the gradual development of and improvement in earthquake early warning systems
(EEWS), more accurate real-time seismic intensity measurements (IMs) methods are needed …
(EEWS), more accurate real-time seismic intensity measurements (IMs) methods are needed …
A deep neural network framework for real‐time on‐site estimation of acceleration response spectra of seismic ground motions
Various earthquake early warning (EEW) methodologies have been proposed globally for
speedily estimating information (ie, location, magnitude, ground‐shaking intensities, and/or …
speedily estimating information (ie, location, magnitude, ground‐shaking intensities, and/or …
Peak ground acceleration prediction for on-site earthquake early warning with deep learning
Y Liu, Q Zhao, Y Wang - Scientific reports, 2024 - nature.com
Rapid and accurate prediction of peak ground acceleration (PGA) is an important basis for
determining seismic damage through on-site earthquake early warning (EEW). The current …
determining seismic damage through on-site earthquake early warning (EEW). The current …
Employing machine learning for seismic intensity estimation using a single station for earthquake early warning
An earthquake early-warning system (EEWS) is an indispensable tool for mitigating loss of
life caused by earthquakes. The ability to rapidly assess the severity of an earthquake is …
life caused by earthquakes. The ability to rapidly assess the severity of an earthquake is …
On-site alert-level earthquake early warning using machine-learning-based prediction equations
J Song, J Zhu, Y Wang, S Li - Geophysical Journal International, 2022 - academic.oup.com
To rapidly and accurately provide alerts at target sites near the epicentre, we develop an on-
site alert-level earthquake early warning (EEW) strategy involving P-wave signals and …
site alert-level earthquake early warning (EEW) strategy involving P-wave signals and …
Prediction of PGA in earthquake early warning using a long short-term memory neural network
A Wang, S Li, J Lu, H Zhang, B Wang… - Geophysical Journal …, 2023 - academic.oup.com
Peak ground acceleration (PGA) is a key parameter used in earthquake early warning
systems to measure the ground motion strength and initiate emergency protocols at major …
systems to measure the ground motion strength and initiate emergency protocols at major …
Threshold-based earthquake early warning for high-speed railways using deep learning
J Zhu, W Sun, S Li, K Yao, J Song - Reliability Engineering & System Safety, 2024 - Elsevier
Earthquakes are disasters that threaten the operational safety of high-speed railways. To
obtain reliable alerts for the earthquake monitoring and early warning systems of high-speed …
obtain reliable alerts for the earthquake monitoring and early warning systems of high-speed …
Hybrid deep-learning network for rapid on-site peak ground velocity prediction
J Zhu, S Li, J Song - IEEE Transactions on Geoscience and …, 2022 - ieeexplore.ieee.org
Rapidly and accurately predicting on-site peak ground velocity (PGV) is important for
earthquake hazard mitigation. Traditional methods used to predict PGV involve a single …
earthquake hazard mitigation. Traditional methods used to predict PGV involve a single …
Continuous prediction of onsite PGV for earthquake early warning based on least squares support vector machine
S **dong, YU Cong, LI Shanyou - Chinese Journal of Geophysics, 2021 - dsjyj.com.cn
In order to improve the accuracy and continuity of the on-site instrumental seismic intensity
prediction, studying the PGV continuous prediction model for earthquake early warning …
prediction, studying the PGV continuous prediction model for earthquake early warning …