震级(天文学)
地震学
地震模拟
地震伤亡估计
地震震级
预警系统
地质学
地震预报
估计
地震预警系统
峰值地面加速度
计算机科学
地震情景
地震灾害
电信
地震动
工程类
数学
天文
系统工程
几何学
物理
缩放比例
作者
Aarón Cofré,Marcelo Marín,Oscar Vásquez Pino,Nicolas Galleguillos,Sebastián Riquelme,Sergio Barrientos,Néstor Becerra Yoma
标识
DOI:10.1109/lgrs.2022.3175108
摘要
In this paper, a method based on Long Short-Term Memory is presented to address the problem of earthquake magnitude estimation for earthquake early warning (EEW) and tsunami early warning (TW) purposes using a seismic station. An end-to-end based scheme is adopted, and a particular attention is paid to compute the magnitude of seismic events larger than M6 and reduce the effective time for TW. More so, these earthquakes are the ones that cause more fear or uncertainty in the population with provision of the most significant destructive potential. However, the occurrence of large earthquakes is low, but to counteract the drawback of limited training data, engineered features were also proposed. The earthquake magnitude relative error estimation reported here in experiments with Chilean seismic data was 4.01% and 8.04% with earthquakes M4.0 or larger (up to M8.1) and M4.0 or smaller, respectively, by employing seismic traces in the nearest station to the corresponding seismic event. The average earthquake-nearest station distance was 196 km and in 26% of the data this distance was greater than 200 km. These results are competitive with those published elsewhere and suggest the possibility to reduce the time required for EEW and specially TW.
科研通智能强力驱动
Strongly Powered by AbleSci AI