基于支持向量机的2021年2月13日日本福岛近海M_(j)7.3级地震震级估算

Magnitude estimation for the February 13,2021 M_(j)7.3 earthquake near the coast of Fukushima Japan based on support vector machine

2021年2月13日日本福岛县近海发生M_(j)7.3级地震,触发了日本气象厅地震预警系统,系统在首台触发后5.6s发出震级为M_(j)6.3级的预警第1报,首台触发后10s对公众发布警报、预警震级为M_(j)6.4级。基于多类型特征参数输入的机器学习支持向量机震级估算模型(SVM-M),利用2021年2月13日日本福岛县近海M_(j)7.3级地震获取的日本K-net强震动观测数据,分析SVM-M模型在该次地震中首台触发初期(首台触发后1~10s)的震级估算效能。结果表明:SVM-M震级估算模型,在首台触发后1s即可给出M_(j)6.3级的震级估算结果,与日本气象厅在首台触发后5.6s发布的预警第1报震级相同;随着时间窗的增加,首台触发后5s和10s,SVM-M模型的震级估算结果分别是M_(j)6.7级和M_(j)6.6级,均大于日本气象厅首台触发后10s对公众发布警报的预警震级。该次地震的离线模拟结果表明:SVM-M模型可在地震发生初期有效提高地震预警震级确定的准确性和时效性。

The earthquake early warning(EEW)system of the Japan Meteorological Agency was triggered by the M_(j)7.3 earthquake off the coast of Fukushima,Japan on February 13,2021.The system issued first alarm with a magnitude of M_(j)6.3 at 5.6 seconds after the first station was triggered,and a magnitude of M_(j)6.4 was issued to the public at 10 seconds after the first station was triggered.In this paper,the support vector machine magnitude estimation model(SVM-M)based on several types of characteristic parameters inputs via machine learning is used to analyze the magnitude estimation performance at the initial trigger stage of the first station(1-10 seconds after the first station is triggered)in this earthquake by using the Japanese K-net strong motion observation data obtained from the M_(j)7.3 earthquake off the coast of Fukushima,Japan on February 13,2021.The results show that the SVM-M model can obtain the magnitude of M_(j)6.3 at 1 second after the first station is triggered,which is the same as the magnitude of the first alarm issued by the Japan Meteorological Agency at 5.6 seconds after the first station is triggered.With the increase of the time window,5 seconds and 10 seconds after the first station was triggered,the estimated magnitude of the SVM-M model was M_(j)6.7 and M_(j)6.6 respectively,both larger than the magnitude of the alarm issued to the public at 10 seconds after the first station was triggered by the Japan Meteorological Agency.The off-line simulation results of this earthquake show that the SVM-M model can effectively improve the accuracy and timeliness of EEW magnitude determination in the early stage of earthquake occurrence.