EMPLOYMENT OF THE RE-SAMPLING ANALYSIS IN DEVELOPMENT OF THE BOORE-ATKINSON 2008 GROUND MOTION PREDICTION EQUATION

Selection of Ground Motion Prediction Equation (GMPE) is one of the key elements within a seismic hazard analysis. A variety of available GMPE models makes this selection a scientific challenge. Therefore, the stability assessment of an optimized GMPE model is investigated in this paper by employing a new Re-Sampling Analysis (RSA) methodology (Azarbakht et al., 2014). The Boore and Atkinson 2008 GMPE is examined in this paper. The multi-objective Genetic Algorithm (GA) is employed in order to minimize the Log-likelihood (LLH) measure as well as maximise the RSA. The ground motion database, in this study, consists of 15348 ground motion spectra resulting from 58 seismic events. The magnitude range is between 5 and 7.4, and all the records have the distance less than 200 km. The analysis is performed for peak ground acceleration. The results are compared with the eight most common NGA GMPEs. The obtained results show that the optimum coefficients for the BA2008 model improve it in such a way that the LLH is least among the models, and the RSA measure is adequate. It is worth mentioning that all the results in this paper are constrained to the given assumptions as well as the considered methodologies and database. The results may change by using different databases and enrichment of the data during future researches.