|
|
|
|
|
Zebin Luo, Mingbo Yang, Xiaocheng Zhou, Guiping Liu, Jinlong Liang, Zhe Liu, Peixue Hua, Jingchen Ma, Leyin Hu, Xiaoru Sun, Bowen Cui, Zhiguo Wang and Yuxuan Chen
The energy inside the Earth can not only be released outward through earthquakes and volcanoes but also can be used by humans in the form of geothermal energy. Is there a correlation between different forms of energy release? In this contribution, we per...
ver más
|
|
|
|
|
|
|
|
|
|
|
Alexey Zavyalov and Eleftheria Papadimitriou
|
|
|
|
|
|
|
|
|
|
|
Sepideh J. Rastin, David A. Rhoades, Christopher Rollins and Matthew C. Gerstenberger
Strain rates have been included in multiplicative hybrid modelling of the long-term spatial distribution of earthquakes in New Zealand (NZ) since 2017. Previous modelling has shown a strain rate model to be the most informative input to explain earthquak...
ver más
|
|
|
|
|
|
|
|
|
|
|
Cristiano Fidani
A correlation between low L-shell 30?100 keV electrons precipitating into the atmosphere and M = 6 earthquakes in West Pacific was presented in past works where ionospheric events anticipated earthquakes by 1.5?3.5 h. This was a statistical result obtain...
ver más
|
|
|
|
|
|
|
|
|
|
|
Matteo Taroni, Giorgio Vocalelli and Andrea De Polis
We introduce a novel approach to estimate the temporal variation of the b-value parameter of the Gutenberg?Richter law, based on the weighted likelihood approach. This methodology allows estimating the b-value based on the full history of the available d...
ver más
|
|
|
|
|
|
|
|
|
|
|
Matteo Picozzi and Antonio Giovanni Iaccarino
Earthquakes prediction is considered the holy grail of seismology. After almost a century of efforts without convincing results, the recent raise of machine learning (ML) methods in conjunction with the deployment of dense seismic networks has boosted ne...
ver más
|
|
|
|
|
|
|
|
|
|
|
Dedalo Marchetti, Angelo De Santis, Saioa A. Campuzano, Maurizio Soldani, Alessandro Piscini, Dario Sabbagh, Gianfranco Cianchini, Loredana Perrone and Martina Orlando
This work presents an analysis of the ESA Swarm satellite magnetic data preceding the Mw = 7.1 California Ridgecrest earthquake that occurred on 6 July 2019. In detail, we show the main results of a procedure that investigates the track-by-track residual...
ver más
|
|
|
|
|
|
|
|
|
|
|
Eugenio Lippiello, Alessandra Cirillo, Cataldo Godano, Elefetheria Papadimitriou and Vassilis Karakostas
A growing interest appears among public authorities and society in accurate and nearly real time aftershock forecasting to manage and mitigate post-seismic risk. Existing methods for aftershock forecasting are strongly affected by the incompleteness of t...
ver más
|
|
|
|
|
|
|
|
|
|
|
Valeri G. Gitis and Alexander B. Derendyaev
In this paper, we suggest two machine learning methods for seismic hazard forecast. The first method is used for spatial forecasting of maximum possible earthquake magnitudes (Mmax" role="presentation">????????Mmax
M
m
a
x
), whereas the second is used f...
ver más
|
|
|
|
|
|