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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 …
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 …
A regionalized partially nonergodic ground-motion model for subduction earthquakes using the NGA-Sub database
NM Kuehn, Y Bozorgnia, KW Campbell… - Earthquake …, 2023 - journals.sagepub.com
In this study, we derived a regionalized partially nonergodic empirical ground-motion model
(GMM) for subduction interface and intraslab earthquakes using an extensive global …
(GMM) for subduction interface and intraslab earthquakes using an extensive global …
Surrogate model‐aided global sensitivity analysis framework for seismic consequences estimation in buildings
J Du, W Wang - Earthquake Engineering & Structural …, 2024 - Wiley Online Library
Seismic consequences estimation for individual buildings is valuable for various
stakeholders, including government entities, building owners, and insurers. The robustness …
stakeholders, including government entities, building owners, and insurers. The robustness …
[HTML][HTML] Interpretability and spatial efficacy of a deep-learning-based on-site early warning framework using explainable artificial intelligence and geographically …
Earthquakes pose significant risks globally, necessitating effective seismic risk mitigation
strategies like earthquake early warning (EEW) systems. However, develo** and …
strategies like earthquake early warning (EEW) systems. However, develo** and …
Ground motion models for Fourier amplitude spectra and response spectra using Machine learning techniques
Y Meenakshi, V Sreenath, R STG - Earthquake Engineering & …, 2024 - Wiley Online Library
One of the main objectives in engineering seismology or in seismic hazard studies is to
estimate the possible ground motion for a given earthquake scenario. In the sparse data …
estimate the possible ground motion for a given earthquake scenario. In the sparse data …
[HTML][HTML] Multi-model seismic susceptibility assessment of the 1950 great Assam earthquake in the Eastern Himalayan front
The seismic susceptibility and mitigation management is paramount concern in tectonically
active area like Northeastern India. This area has been devastated innumerably during the …
active area like Northeastern India. This area has been devastated innumerably during the …
Accelerating low-frequency ground motion simulation for finite fault sources using neural networks
In the context of early emergency response to moderate and large earthquake shaking, we
present a simulation based low-frequency ground motion estimation workflow that expedites …
present a simulation based low-frequency ground motion estimation workflow that expedites …
Structural failure analysis with CMS-based ground motion selection using innovative cost function and weight factors
The selection and scaling of ground motion records is considered a primary and essential
task in performing structural analysis and design. Conventional methods involve using …
task in performing structural analysis and design. Conventional methods involve using …
Hybrid convolutional neural network approach for optimizing automatic identification of natural isotopes in gamma ray environmental sample spectra
B Paleti, GH Sastry - Neural Computing and Applications, 2024 - Springer
Radioisotope identification presents challenges that can be effectively addressed through
pattern recognition and machine learning (ML) techniques. However, further investigation is …
pattern recognition and machine learning (ML) techniques. However, further investigation is …