Results 51 to 60 of about 2,665,652 (228)

Influence of Site Amplification Approaches in PSRA: Insights From Five Different Cities

Earthquake Spectra, Volume 42, Issue 4, November 2026.
Regional and national seismic hazard models used in probabilistic seismic risk analysis often rely on generalized proxy‐based site terms to account for ground shaking amplification. This can result in coarse representations of site response, which can introduce bias or additional uncertainty in the associated risk results.
Julián Montejo, Vitor Silva, Bruno Pace, Marco Pagani   +3 more
wiley   +1 more source

The Growth of Earthquake Clusters

Frontiers in Earth Science, 2021
Migration of hypocenters is a common attribute of induced injection seismicity and of earthquake swarms, which distinguishes them from aftershock sequences.
Tomas Fischer, Sebastian Hainzl
doaj   +1 more source

Fourier Shell Analysis: k‐Space‐Based Metrics for Assessing Super‐Resolution in 4D Flow MRI

Magnetic Resonance in Medicine, Volume 96, Issue 4, Page 1983-1990, October 2026.
ABSTRACT Purpose To support the emerging field of super‐resolution (SR) in 4D flow MRI by proposing Fourier shell analysis to disentangle resolution enhancement from denoising effects during evaluation. Methods A thoracic aortic 4D flow MRI dataset was synthesized with various degrees of stenosis, providing ground truth flow fields generated using ...
Luuk Jacobs, Pietro Dirix, Sebastian Kozerke   +2 more
wiley   +1 more source

Common dependence on stress for the two fundamental laws of statistical seismology

Nature, 2009
Two of the long-standing relationships of statistical seismology are power laws: the Gutenberg-Richter relation describing the earthquake frequency-magnitude distribution, and the Omori-Utsu law characterizing the temporal decay of aftershock rate following a main shock.
Narteau, Clément, Byrdina, Svetlana, Shebalin, Peter, Schorlemmer, Danijel   +3 more
openaire   +3 more sources

A Spatio‐Temporal Neural Kernel Function Model for Earthquake Clustering: Bridging ETAS and Neural Point Processes

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 5, October 2026.
Abstract Modeling earthquake clustering in space and time is central to understanding seismicity patterns and improving forecasting. The Epidemic‐Type Aftershock Sequence (ETAS) model, grounded in the Hawkes process, has long been the standard approach for describing aftershock triggering through fixed, empirically defined kernel functions.
Chengxiang Zhan, Stephen Wu, Jiancang Zhuang, Shichen Gao   +3 more
wiley   +1 more source

Earthquake Seismogram Denoising Across Time, Time‐Frequency, and Hybrid Domain Approaches

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 5, October 2026.
Abstract Deep learning earthquake signal denoisers commonly operate directly on waveform data or on time‐frequency representations, yet the impact of this design choice has not been systematically assessed under controlled conditions. Here we design and benchmark four comparable deep learning architectures to assess the effect of input data ...
Nikolaj L. Dahmen
wiley   +1 more source

Solving the Woes of Statistical Seismology: The Community On-Line Resource for Statistical Seismicity Analysis (CORSSA)l

, 2007
Solving the Woes of Statistical Seismology: The Community On-Line Resource for Statistical Seismicity Analysis (CORSSA)Istituto Nazionale di Geofisica e Vulcanologia (INGV), Rome, Italy Institute of Statistical Mathematics (ISM), Tokyo, Japan Swiss ...
Felzer, K., Michael, A.J., Schorlemmer, D., Wiemer, S., Woessner, J.   +4 more
core   +2 more sources

Relationship Between the 2019 Ridgecrest, California, M_W7.1 Earthquake and Its M_W6.4 Foreshock Sequence

Entropy
The 2019 Ridgecrest MW7.1 earthquake has received significant attention due to its complex fault activity. It is also noticeable for its MW6.4 foreshock sequence.
Jianchang Zheng, Zhengshuai Zhang, Xiaohan Li   +2 more
doaj   +1 more source

Adapting a Pretrained LLM to Rapidly Recover Earthquake Magnitude and Location

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 5, October 2026.
Abstract Determining earthquake magnitude and location through fast, automated methods is fundamental for seismic monitoring. Recent studies have shown that Large Language Models (LLMs) can operate as pattern‐recognition systems capable of handling novel domains and purely numerical tasks.
Aurora Bassani, Daniele Trappolini, Giulio Poggiali, Elisa Tinti, Fabio Galasso, Alberto Michelini, Chris Marone   +6 more
wiley   +1 more source

A comparison of reflection coefficients in porous media from 2D plane-wave analysis & spectral element forward modeling [PDF]

, 2018
The Biot theory provides a general framework for describing the seismic response of porous media. Proper boundary conditions must be specified for the following three cases: the elastic-poroelastic interface, the acoustic-poroelastic interface and the ...
Peng, H., Sripanich, Y., Trampert, J.A., Seismology, Pires de Vasconcelos, I.   +4 more
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