AUTHOR=Jang Dongil , Ahn Jae-Kwang , Kim Tae-Woong , Kwak Dong Youp 

TITLE=Linearly combined ground motion model using quadratic programming for low- to mid-size seismicity region: South Korea

JOURNAL=Frontiers in Earth Science

VOLUME=Volume 10 - 2022

YEAR=2023

URL=https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2022.1067802

DOI=10.3389/feart.2022.1067802

ISSN=2296-6463

ABSTRACT=This study suggests a linearly combined ground motion model (GMM) optimized for within-rock condition of South Korea. Ground motions recorded by accelerometers positioned in within-rock layers are used as target intensity measures (IM), and five local GMMs and four global GMMs are used as candidates of combination. Optimization which seeks to find a weight vector minimizing the uncertainty of the combined model is performed using the quadratic programming (QP) technique that provides very fast and solid results for linear combination problem. This study illustrates how to utilize the QP technique for the linear combination problem. Also, we suggest optimized weight vectors for GMM combinations for two conditions: 1) the IM prediction of a scenario event without observations; 2) the IM prediction of a past event with observations. Among local and global GMMs considered, JB03, Eea15, JH21, and BSSA14 are selected as the best four GMMs for the 1st condition, and Jea02, JB03, JH21, and CB14 are selected as the best four GMMs for the 2nd condition. The combined model reduces the standard deviation of residuals in natural logarithm as 10% and 8% for 1st and 2nd conditions, respectively, comparing to the best individual GMM at each period. Among GMMs considered, the prediction by Eea15 is only applicable for magnitude less than 5. Hence, for large magnitude (Mw > 5) prediction, CB14 is recommended as replace of Eea15 for the best four models of 1st condition.