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 …

Seismic hazard analyses (SHA) are routinely carried out around the world to understand the
hazard, and consequently the risk, posed by earthquake activity. Whether single scenario …

Abstract The 2013 European Seismic Hazard Model (ESHM13) results from a community-
based probabilistic seismic hazard assessment supported by the EU-FP7 project “Seismic …

This article presents the latest generation of ground-motion models for the prediction of
elastic response (pseudo-) spectral accelerations, as well as peak ground acceleration and …

To complement the new European Strong-Motion dataset and the ongoing efforts to update
the seismic hazard and risk assessment of Europe and Mediterranean regions, we propose …

This article describes the Engineering Strong‐Motion Database (ESM), developed in the
framework of the European project Network of European Research Infrastructures for …

Conventional ground motion models have extensively been established worldwide based
on classical regression analysis of records. Alternatively, advanced nonparametric machine …

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 …

Presented herein is an updated model for empirical prediction of 5%-damped elastic
response spectra in the period range 0–10 s, peak ground acceleration and velocity, based …

Selection and scaling of input ground motion records for nonlinear dynamic analysis of
structures has become an important issue and studies on this subject can provide valuable …