2023
DOI: 10.1016/j.soildyn.2022.107656
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Evaluation of the predictive performance of regional and global ground motion predictive equations against Greek strong motion data

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Cited by 5 publications
(7 citation statements)
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“…Although the selected evaluation approach offers an objective way of ranking the selected GMPMs, it has been observed that different evaluation approaches lead to different rankings, and, therefore, GMPMs for Probabilistic Seismic Hazard Analysis (PSHA) must be combined with corresponding weighting factors, which were finally calculated (Table 1). The same results have been derived from a similar analysis proposed by Sotiriadis and Margaris [53]. Based on the analysis, the first three GMPMs were selected to be implemented for the entire GR/TR cross border area.…”
Section: Ground Motion Prediction Equations and Selection Of Seismic ...mentioning
confidence: 94%
See 1 more Smart Citation
“…Although the selected evaluation approach offers an objective way of ranking the selected GMPMs, it has been observed that different evaluation approaches lead to different rankings, and, therefore, GMPMs for Probabilistic Seismic Hazard Analysis (PSHA) must be combined with corresponding weighting factors, which were finally calculated (Table 1). The same results have been derived from a similar analysis proposed by Sotiriadis and Margaris [53]. Based on the analysis, the first three GMPMs were selected to be implemented for the entire GR/TR cross border area.…”
Section: Ground Motion Prediction Equations and Selection Of Seismic ...mentioning
confidence: 94%
“…Figure 4. Top: Map displaying the GMPM Zones[52][53][54][55][56]58] for the implementation area and their respective geographic coverage. The main provider (NIEP, AFAD, ITSAK) of earthquake related real time data is auto-selected based on the epicenter location of the triggering earthquake and the seismic faults in any of the three area sections.…”
mentioning
confidence: 99%
“…Although the GMPE of Boore et al ( 2021) is currently the most reliable tool to estimate the ground motion in Greece, within the context of PSHA, more GMPEs should be implemented to construct a ground motion logic tree so that the associated epistemic uncertainty is reduced. Recently, [18] evaluated and ranked several GMPEs using the statistical methods of Log-likelihood (LLH) [34], Multivariate LLH [35], and Euclidean Distance Ranking (EDR) [36] and the most updated strong motion dataset for Greece. Their study included multiple ground motion intensity measures, such as the Peak Ground Acceleration (PGA) and Velocity (PGV), as well as some 5%-damped spectral acceleration ordinates (S a ).…”
Section: Ground Motion Modelingmentioning
confidence: 99%
“…Herein, to assess the seismic hazard in REMTH, the approach of Probabilistic Seismic Hazard Assessment (PSHA) [17] is implemented along with the logic tree approach to take into account the uncertainty in both seismic source and ground motion modeling. The selection of the Ground Motion Prediction Equations (GMPEs) is based on the work of Sotiriadis and Margaris (2023) [18], who have evaluated many global, European, and local GMPEs through data-driven methods based on the comparison between their estimates and strong-motion data from Greece. Moreover, various seismic source models that have been proposed during the last few years for Greece are considered in this study.…”
Section: Introductionmentioning
confidence: 99%
“…A comprehensive effort of GMPE ranking for Greece was not performed until very recently, when Sotiriadis and Margaris [85] used the most up-to-date Greek strong motion dataset and evaluated a number of GMPEs using three different approaches. The most widely used goodness-of-fit measures to evaluate the performance of GMPEs (also employed by Sotiriadis and Margaris [85]) are the Log-Likelihood (LLH) method, proposed by Scherbaum et al [86], and the Euclidean Distance-Based Ranking (EDR) scheme, suggested by Kale and Akkar [87]. Every approach has its strengths and inherent deficiencies; hence, the results should be used as an advisory tool for experts, rather than a black-box routine.…”
Section: Evaluation Of the Predictive Perfomance Of Gmpes-gmpe Rankingmentioning
confidence: 99%