The platform will undergo maintenance on Sep 14 at about 7:45 AM EST and will be unavailable for approximately 2 hours.
2015
DOI: 10.1007/978-3-319-16964-4_12
|View full text |Cite
|
Sign up to set email alerts
|

Developments in Ground Motion Predictive Models and Accelerometric Data Archiving in the Broader European Region

Abstract: This paper summarizes the evolution of major strong-motion databases and ground-motion prediction equations (GMPEs) for shallow active crustal regions (SACRs) in Europe and surrounding regions. It concludes with some case studies to show the sensitivity of hazard results at different seismicity levels and exceedance rates for local (developed from country-specific databases) and global (based on databases of multiple countries) GMPEs of the same region. The case studies are enriched by considering other global… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2018
2018
2018
2018

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 45 publications
(31 reference statements)
0
1
0
Order By: Relevance
“…Hellenic Subduction Arc, Cyprian Arc, Makran, Iran). Inherent uncertainties of quality and accuracy of earthquake sources and ground shaking data (Akkar et al 2014) were incorporated by modelling alternative seismogenic source models (Danciu et al 2017). Data driven techniques combined with sensitivity analyses were used when building the reference ground motion model (Danciu et al 2016).…”
Section: Introductionmentioning
confidence: 99%
“…Hellenic Subduction Arc, Cyprian Arc, Makran, Iran). Inherent uncertainties of quality and accuracy of earthquake sources and ground shaking data (Akkar et al 2014) were incorporated by modelling alternative seismogenic source models (Danciu et al 2017). Data driven techniques combined with sensitivity analyses were used when building the reference ground motion model (Danciu et al 2016).…”
Section: Introductionmentioning
confidence: 99%