[1]朱景宝,宋晋东,李山有.基于支持向量机的2021年2月13日日本福岛近海Mj7.3级地震震级估算[J].世界地震工程,2021,(02):074-81.
 ZHU Jingbao,SONG Jindong,LI Shanyou.Magnitude estimation for the February 13, 2021 Mj7.3 earthquake near the coast of Fukushima Japan based on support vector machine[J].,2021,(02):074-81.
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基于支持向量机的2021年2月13日日本福岛近海Mj7.3级地震震级估算
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《世界地震工程》[ISSN:/CN:]

卷:
期数:
2021年02期
页码:
074-81
栏目:
出版日期:
2021-04-30

文章信息/Info

Title:
Magnitude estimation for the February 13, 2021 Mj7.3 earthquake near the coast of Fukushima Japan based on support vector machine
作者:
朱景宝 宋晋东 李山有
中国地震局工程力学研究所, 中国地震局地震工程与工程振动重点实验室, 黑龙江 哈尔滨 150080
Author(s):
ZHU Jingbao SONG Jindong LI Shanyou
Institute of Engineering Mechanics, China Earthquake Administration; Key Laboratory of Earthquake Engineering and Engineering Vibration of China Earthquake Administration, Harbin 150080,China
关键词:
地震预警支持向量机福岛县近海地震震级估算机器学习
Keywords:
earthquake early warningsupport vector machineearthquake near the coast of Fukushimamagnitude estimationmachine learning
分类号:
P315.3P315.7P315.92
摘要:
2021年2月13日日本福岛县近海发生Mj7.3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Mj6.3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Mj6.4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Mj7.3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Mj6.3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Mj6.7级和Mj6.6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。
Abstract:
The earthquake early warning (EEW) system of the Japan Meteorological Agency was triggered by the Mj7.3 earthquake off the coast of Fukushima, Japan on February 13, 2021. The system issued first alarm with a magnitude of Mj6.3 at 5.6 seconds after the first station was triggered, and a magnitude of Mj6.4 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 Mj7.3 earthquake off the coast of Fukushima, Japan on February 13, 2021.The results show that the SVM-M model can obtain the magnitude of Mj6.3 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 Mj6.7 and Mj6.6 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.

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备注/Memo

备注/Memo:
收稿日期:2021-03-15;改回日期:2021-03-26。
基金项目:国家重点研发计划课题(2018YFC1504003);国家自然科学基金项目(51408564)
作者简介:朱景宝(1996-),男,硕士研究生,主要从事机器学习地震预警研究.E-mail:1178750132@qq.com
通讯作者:李山有(1965-),男,博士,研究员,博士生导师,主要从事地震预警研究.E-mail:lishanyou@126.com
更新日期/Last Update: 1900-01-01