Artificial intelligence based real-time earthquake prediction
Earthquake prediction is considered a vital endeavour for human safety. Effective
earthquake prediction can drastically reduce human damage, which is of utmost importance …
earthquake prediction can drastically reduce human damage, which is of utmost importance …
Uniformly processed Fourier spectra amplitude database for recently compiled New Zealand strong ground motions
We present a ground‐motion parameter database for earthquakes recorded between 2000
and the end of 2022 in New Zealand, which was developed within the New Zealand …
and the end of 2022 in New Zealand, which was developed within the New Zealand …
Recent advances in earthquake seismology using machine learning
Given the recent developments in machine-learning technology, its application has rapidly
progressed in various fields of earthquake seismology, achieving great success. Here, we …
progressed in various fields of earthquake seismology, achieving great success. Here, we …
SeisT: A foundational deep learning model for earthquake monitoring tasks
S Li, X Yang, A Cao, C Wang, Y Liu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Seismograms, the fundamental seismic records, have revolutionized earthquake research
and monitoring. Recent advancements in deep learning have further enhanced seismic …
and monitoring. Recent advancements in deep learning have further enhanced seismic …
A Hybrid Deep Learning Model for Rapid Probabilistic Earthquake Source Parameter Estimation With Displacement Waveforms From a Flexible Set of Seismic or HR …
X Lin, C Xu, G Jiang, J Zang - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The prompt and reliable determination of seismic source parameters, which provide
information on earthquake location (LOC), magnitude (MAG), and focal mechanism (FM), is …
information on earthquake location (LOC), magnitude (MAG), and focal mechanism (FM), is …
Integration of Machine learning and equal differential time method for enhanced hypocenter localization in earthquake early warning systems: application to dense …
Abstract The Earthquake Early Warning System (EEWS) acts as a vital instrument for
reducing seismic risks in regions with high seismic vulnerability. A rapid and accurate …
reducing seismic risks in regions with high seismic vulnerability. A rapid and accurate …
Evaluating automated seismic event detection approaches: An application to Victoria Land, East Antarctica
As seismic data collection continues to grow, advanced automated processing techniques
for robust phase identification and event detection are becoming increasingly important …
for robust phase identification and event detection are becoming increasingly important …
CSESnet: A deep learning P-wave detection model based on UNet++ designed for China Seismic Experimental Site
B Li, L Fan, C Jiang, S Liao, L Fang - Frontiers in Earth Science, 2023 - frontiersin.org
Accurate detection of P-wave arrivals has important applications in real-time seismic data
processing, such as earthquake monitoring and earthquake early warning. The Sichuan and …
processing, such as earthquake monitoring and earthquake early warning. The Sichuan and …
A supervised machine learning approach for estimating plate interface locking: Application to Central Chile
S Barra, M Moreno, F Ortega-Culaciati… - Physics of the Earth and …, 2024 - Elsevier
Estimating locking degree at faults is important for determining the spatial distribution of slip
deficit at seismic gaps. Inverse methods of varying complexity are commonly used to …
deficit at seismic gaps. Inverse methods of varying complexity are commonly used to …
RockNet: Rockfall and earthquake detection and association via multitask learning and transfer learning
Seismological data plays a crucial role in timely slope failure hazard assessments. However,
identifying rockfall waveforms from seismic data poses challenges due to their high …
identifying rockfall waveforms from seismic data poses challenges due to their high …