Modelling the spatial correlation of earthquake ground motion: Insights from the literature, data from the 2016–2017 Central Italy earthquake sequence and ground …

E Schiappapietra, J Douglas - Earth-science reviews, 2020 - Elsevier
Over the past decades, researchers have given increasing attention to the modelling of the
spatial correlation of earthquake ground motion intensity measures (IMs), particularly when …

How to Price Catastrophe Bonds for Sustainable Earthquake Funding? A Systematic Review of the Pricing Framework

RA Ibrahim, Sukono, H Napitupulu, RI Ibrahim - Sustainability, 2023 - mdpi.com
Earthquake contingency costs in traditional insurance cannot provide sufficient earthquake
funding for a country because they often differ significantly from actual losses. Over the last …

Pan-European ground-motion prediction equations for the average horizontal component of PGA, PGV, and 5%-damped PSA at spectral periods up to 3.0 s using the …

D Bindi, M Massa, L Luzi, G Ameri, F Pacor… - Bulletin of Earthquake …, 2014 - Springer
This article presents a set of Ground-Motion Prediction Equations (GMPEs) for Europe and
the Middle East, derived from the RESORCE strong motion data bank, following a standard …

Rapid prediction of earthquake ground shaking intensity using raw waveform data and a convolutional neural network

D Jozinović, A Lomax, I Štajduhar… - Geophysical Journal …, 2020 - academic.oup.com
This study describes a deep convolutional neural network (CNN) based technique to predict
intensity measurements (IMs) of earthquake ground shaking. The input data to the CNN …

The new Italian seismic hazard model (MPS19)

C Meletti, W Marzocchi, V D'amico… - Annals of …, 2021 - gfzpublic.gfz-potsdam.de
We describe the main structure and outcomes of the new probabilistic seismic hazard model
for Italy, MPS19 [Modello di Pericolosità Sismica, 2019]. Besides to outline the probabilistic …

Seismic amplification maps of Italy based on site-specific microzonation dataset and one-dimensional numerical approach

G Falcone, G Acunzo, A Mendicelli, F Mori, G Naso… - Engineering …, 2021 - Elsevier
Prediction of surface ground motion based on advanced approaches is a non-trivial task at
large area. In fact, advanced approaches require a detailed geological and geotechnical …

A nonergodic ground‐motion model for California with spatially varying coefficients

N Landwehr, NM Kuehn, T Scheffer… - Bulletin of the …, 2016 - pubs.geoscienceworld.org
Traditional probabilistic seismic‐hazard analysis as well as the estimation of ground‐motion
models (GMM s) is based on the ergodic assumption, which means that the distribution of …

Strong correlation between stress drop and peak ground acceleration for recent M 1–4 earthquakes in the San Francisco Bay area

DT Trugman, PM Shearer - Bulletin of the Seismological …, 2018 - pubs.geoscienceworld.org
Theoretical and observational studies suggest that between‐event variability in the median
ground motions of larger (M≥ 5) earthquakes is controlled primarily by the dynamic …

A revised ground‐motion prediction model for shallow crustal earthquakes in Italy

G Lanzano, L Luzi, F Pacor… - Bulletin of the …, 2019 - pubs.geoscienceworld.org
This work aims to revise the Bindi et al.(2011) ground‐motion model for shallow crustal
earthquakes in Italy (hereinafter, ITA10), calibrated in the magnitude range 4.0–6.9 using …

Transfer learning: Improving neural network based prediction of earthquake ground shaking for an area with insufficient training data

D Jozinović, A Lomax, I Štajduhar… - Geophysical Journal …, 2022 - academic.oup.com
In a recent study, we showed that convolutional neural networks (CNNs) applied to network
seismic traces can be used for rapid prediction of earthquake peak ground motion intensity …