The promise of implementing machine learning in earthquake engineering: A state-of-the-art review
Machine learning (ML) has evolved rapidly over recent years with the promise to
substantially alter and enhance the role of data science in a variety of disciplines. Compared …
substantially alter and enhance the role of data science in a variety of disciplines. Compared …
The 2018 update of the US National Seismic Hazard Model: Overview of model and implications
MD Petersen, AM Shumway, PM Powers… - Earthquake …, 2020 - journals.sagepub.com
During 2017–2018, the National Seismic Hazard Model for the conterminous United States
was updated as follows:(1) an updated seismicity catalog was incorporated, which includes …
was updated as follows:(1) an updated seismicity catalog was incorporated, which includes …
Application of a new machine learning model to improve earthquake ground motion predictions
A cross-region prediction model named SeisEML (an acronym for Seismological Ensemble
Machine Learning) has been developed in this paper to predict the peak ground …
Machine Learning) has been developed in this paper to predict the peak ground …
Regional seismic risk and resilience assessment: Methodological development, applicability, and future research needs–An earthquake engineering perspective
Given the devastating losses incurred by past major earthquake events together with the
ever-increasing global seismic exposures due to population growth and urbanization …
ever-increasing global seismic exposures due to population growth and urbanization …
NGA-West2 ground motion model for the average horizontal components of PGA, PGV, and 5% damped linear acceleration response spectra
KW Campbell, Y Bozorgnia - Earthquake Spectra, 2014 - journals.sagepub.com
We used an expanded PEER NGA-West2 database to develop a new ground motion
prediction equation (GMPE) for the average horizontal components of PGA, PGV, and 5 …
prediction equation (GMPE) for the average horizontal components of PGA, PGV, and 5 …
NGA-subduction global ground motion models with regional adjustment factors
We develop semi-empirical ground motion models (GMMs) for peak ground acceleration,
peak ground velocity, and 5%-damped pseudo-spectral accelerations for periods from 0.01 …
peak ground velocity, and 5%-damped pseudo-spectral accelerations for periods from 0.01 …
Classifying earthquake damage to buildings using machine learning
The ability to rapidly assess the spatial distribution and severity of building damage is
essential to post-event emergency response and recovery. Visually identifying and …
essential to post-event emergency response and recovery. Visually identifying and …
NGA-West2 research project
Y Bozorgnia, NA Abrahamson, LA Atik… - Earthquake …, 2014 - journals.sagepub.com
The NGA-West2 project is a large multidisciplinary, multi-year research program on the Next
Generation Attenuation (NGA) models for shallow crustal earthquakes in active tectonic …
Generation Attenuation (NGA) models for shallow crustal earthquakes in active tectonic …
On the application of machine learning techniques to derive seismic fragility curves
Deriving the fragility curves is a key step in seismic risk assessment within the performance-
based earthquake engineering framework. The objective of this study is to implement …
based earthquake engineering framework. The objective of this study is to implement …
Development of the 2017 national seismic hazard maps of Indonesia
Indonesia is one of the most seismically active countries in the world, and its large,
vulnerable population makes reliable seismic hazard assessment an urgent priority. In 2016 …
vulnerable population makes reliable seismic hazard assessment an urgent priority. In 2016 …