Results 121 to 130 of about 95,361 (334)

Preface to the Focus Section on Machine Learning in Seismology

open access: yesSeismological Research Letters, 2019
Machine learning (ML) is a collection of algorithms and statistical models that enable computers to extract relevant patterns and information from large data sets.
K. Bergen, Ting Chen, Zefeng Li
semanticscholar   +1 more source

Common Sensor Platform Project

open access: yesPerspectives of Earth and Space Scientists, Volume 6, Issue 1, December 2025.
Abstract EarthScope Consortium's Common Sensor Platform (CSP) project is a unified, modular, and scalable design approach for geophysical instrumentation deployments. Developed through cross disciplinary collaboration of National Science Foundation's GAGE and SAGE facilities, the platform outlines core station subsystems that have the flexibility to be
Molly Staats   +14 more
wiley   +1 more source

Advances in 6C seismology: Applications of combined translational and rotational motion measurements in global and exploration seismology

open access: yes, 2018
Over the past few decades, the potential of collocated measurements of 6C data (3C of translational and 3C of rotational motion) has been demonstrated in global seismology using high-sensitivity, observatory-based ring laser technology.
C. Schmelzbach   +9 more
semanticscholar   +1 more source

Modelling the Importance of Ground and Strong‐Motion Variables on the Damage Status in the 2023 Kahramanmaraş Earthquakes Using Supervised Machine Learning

open access: yesGeoscience Data Journal, Volume 12, Issue 4, October 2025.
KNN achieved the highest performance (0.989) using the full dataset and 0.988 with ground‐based parameters. EBd and f0 were key contributors to damage, while PGA dominated strong‐motion models. Specificity consistently outperformed sensitivity in earthquake‐parameter models.
Mustafa Senkaya   +3 more
wiley   +1 more source

Ionospheric VTEC anomalies before Ms7.1 Yushu earthquake

open access: yesGeodesy and Geodynamics, 2011
Vertical total electron content is examined to check whether the Ms7.1 Yushu earthquake on April 14, 2010, may have caused any anomalous ionospheric changes. The result shows two TEC increases over the epicenter vicinity on April 1 and 5; these anomalies
Xiong Jing, Zhou Yiyan, Wu Yun
doaj   +1 more source

ARL‐Unbiased Exponential Control Charts With Estimated Parameters: Statistical Design and Implementation

open access: yesQuality and Reliability Engineering International, Volume 41, Issue 6, Page 2587-2600, October 2025.
ABSTRACT The bias of a control chart is an important factor in practical applications. Average run length (ARL)‐biased control charts have their out‐of‐control (OOC) ARL (ARLOOC) greater than the in‐control (IC) ARL (ARLin) for some values of the monitored parameter.
Nirpeksh Kumar, Subha Chakraborti
wiley   +1 more source

Red giant seismology: Observations

open access: yesEPJ Web of Conferences, 2013
The CoRoT and Kepler missions provide us with thousands of red-giant light curves that allow a very precise asteroseismic study of these objects. Before CoRoT and Kepler, the red-giant oscillation patterns remained obscure.
Mosser B.
doaj   +1 more source

Determination of the cross-field density structuring in coronal waveguides using the damping of transverse waves

open access: yes, 2014
Time and spatial damping of transverse magnetohydrodynamic (MHD) kink oscillations is a source of information on the cross-field variation of the plasma density in coronal waveguides.
Arregui, I., Ramos, A. Asensio
core   +1 more source

“Lab‐Quakes”: Quantifying the Complete Energy Budget of High‐Pressure Laboratory Failure

open access: yesAGU Advances, Volume 6, Issue 5, October 2025.
Abstract Understanding the interplay of various energy sinks during seismic fault slip is essential for advancing earthquake physics and improving hazard assessment. However, quantifying the energy consumed by major dissipative processes remains a challenge.
Daniel Ortega‐Arroyo   +7 more
wiley   +1 more source

Home - About - Disclaimer - Privacy