Exploring Challenges in Deep Learning of Single-Station Ground Motion Records

arXiv:2403.07569v1 Announce Type: cross
Abstract: Contemporary deep learning models have demonstrated promising results across various applications within seismology and earthquake engineering. These models rely primarily on utilizing ground motion records for tasks such as earthquake event classification, localization, earthquake early warning systems, and structural health monitoring. However, the extent to which these models effectively learn from these complex time-series signals has not been thoroughly analyzed. In this study, our objective is to evaluate the degree to which auxiliary information, such …

abstract applications arxiv challenges classification cs.cv cs.lg deep learning earthquake eess.sp engineering event health however localization monitoring records results seismology systems tasks type