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Seyed Mehdi Mousavi

Seyed Mehdi Mousavi

Academic rank: Assistant Professor
ORCID:
Education: PhD.
ScopusId: 36806793700
Faculty: Engineering
Address: Arak University
Phone:

Research

Title
Applicability of different ground-motion prediction models for northern Iran
Type
JournalPaper
Keywords
Ground-motion prediction equations  Evaluation of fitness  Ranking  PSHA  Northern Iran
Year
2014
Journal Natural Hazards
DOI
Researchers Hamid Zafarani ، Seyed Mehdi Mousavi

Abstract

A total of 163 free-field acceleration time histories recorded at epicentral distances of up to 200 km from 32 earthquakes with moment magnitudes ranging from Mw 4.9 to 7.4 have been used to investigate the predictive capabilities of the local, regional, and next generation attenuation (NGA) ground-motion prediction equations and determine their applicability for northern Iran. Two different statistical approaches, namely the likelihood method (LH) of Scherbaum et al. (Bull Seismol Soc Am 94:341–348, 2004) and the average log-likelihood method (LLH) of Scherbaum et al. (Bull Seismol Soc Am 99:3234–3247, 2009), have been applied for evaluation of these models. The best-fitting models (considering both the LH and LLH results) over the entire frequency range of interest are those of Ghasemi et al. (Seismol 13:499–515, 2009a) and Soghrat et al. (Geophys J Int 188:645–679, 2012) among the local models, Abrahamson and Silva (Earthq Spectra 24:67–97, 2008) and Chiou and Youngs (Earthq Spectra 24:173–215, 2008) among the NGA models, and finally Akkar and Bommer (Seism Res Lett 81:195–206, 2010) among the regional models.