Seismic intensity estimation for earthquake early warning using optimized machine learning model

MS Abdalzaher, MS Soliman… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
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 …

Employing machine learning for seismic intensity estimation using a single station for earthquake early warning

MS Abdalzaher, MS Soliman, M Krichen, MA Alamro… - Remote Sensing, 2024 - mdpi.com
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 …

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 …

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 …

[HTML][HTML] Interpretability and spatial efficacy of a deep-learning-based on-site early warning framework using explainable artificial intelligence and geographically …

J Fayaz, C Galasso - Geoscience Frontiers, 2024 - Elsevier
Earthquakes pose significant risks globally, necessitating effective seismic risk mitigation
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 …

[HTML][HTML] Multi-model seismic susceptibility assessment of the 1950 great Assam earthquake in the Eastern Himalayan front

A Bhadran, BP Duarah, D Girishbai, AL Achu… - Geosystems and …, 2024 - Elsevier
The seismic susceptibility and mitigation management is paramount concern in tectonically
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

L Lehmann, M Ohrnberger, M Metz… - Geophysical Journal …, 2023 - academic.oup.com
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 …

Structural failure analysis with CMS-based ground motion selection using innovative cost function and weight factors

D Samadian, IB Muhit, N Dawood - Earthquake Engineering and …, 2024 - Springer
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 …

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 …