南方科技大学知识苑(SUSTech KC): Autonomous Earthquake Location via Deep Reinforcement Learning

题名	Autonomous Earthquake Location via Deep Reinforcement Learning
作者	Kuang, Wenhuan1,2,3 ; Yuan, Congcong 4; Zou, Zhihui 1; Zhang, Jie 5; Zhang, Wei2,3
通讯作者	Zhang, Wei
发表日期	2024
DOI	10.1785/0220230118
发表期刊	SEISMOLOGICAL RESEARCH LETTERS 影响因子和分区
ISSN	0895-0695
EISSN	1938-2057
卷号	95 期号:1
摘要	Recent advances in artificial intelligence allow seismologists to upgrade the workflow for locating earthquakes. The standard workflow concatenates a sequence of data processing modules, including event detection, phase picking, association, and event location, with elaborately fine-tuned parameters, lacking automation and convenience. Here, we leverage deep reinforcement learning and develop a state-of-theart earthquake robot (EQBot) to help advance automated earthquake location. The EQBot learns from tremendous trial-and-error explorations, which aims to best align the observed P and S waves, complying with the geophysical principle of gather alignments in source imaging. After training on earthquakes (M >= 2.0) for a decade in the Los Angeles region, it can locate earthquakes directly from waveforms with mean absolute errors of 1.32 km, 1.35 km, and 1.96 km in latitude, longitude, and depth, respectively, closely comparable to the cataloged locations. Moreover, it can automatically implement quality control by examining the alignments of P and S waves. Our study provides a new solution to advance the earthquake location process toward full automation.
相关链接	[来源记录]
收录类别	SCI ; EI
语种	英语
学校署名	通讯
资助项目	National Key R&D Program of China[2021YFC3000703-05] ; National Natural Science Foundation of China["42104047","U1901602"] ; Guangdong Provincial Key Laboratory of Geophysical High-resolution Imaging Technology[2022B1212010002] ; Shenzhen Science and Technology Program[KQTD20170810111725321] ; Guangdong Provincial Pearl River Talents Program[2019QN01G801]
WOS研究方向	Geochemistry & Geophysics
WOS类目	Geochemistry & Geophysics
WOS记录号	WOS:001198686600001
出版者	SEISMOLOGICAL SOC AMER
ESI学科分类	GEOSCIENCES
来源库	Web of Science
引用统计
成果类型	期刊论文
条目标识符	http://sustech.caswiz.com/handle/2SGJ60CL/788624
专题	理学院_地球与空间科学系南方科技大学
作者单位	1.Ocean Univ China, Coll Marine Geosci, Key Lab Submarine Geosci & Prospecting Tech, MOE, Qingdao, Peoples R China 2.Southern Univ Sci & Technol, Dept Earth & Space Sci, Shenzhen, Peoples R China 3.Southern Univ Sci & Technol, Guangdong Prov Key Lab Geophys High Resolut Imagin, Shenzhen, Peoples R China 4.Harvard Univ, Dept Earth & Planetary Sci, Cambridge, MA USA 5.Univ Sci & Technol China, Dept Geophys, Hefei, Peoples R China
第一作者单位	地球与空间科学系; 南方科技大学
通讯作者单位	地球与空间科学系; 南方科技大学
推荐引用方式 GB/T 7714	Kuang, Wenhuan,Yuan, Congcong,Zou, Zhihui,et al. Autonomous Earthquake Location via Deep Reinforcement Learning[J]. SEISMOLOGICAL RESEARCH LETTERS,2024,95(1).
APA	Kuang, Wenhuan,Yuan, Congcong,Zou, Zhihui,Zhang, Jie,&Zhang, Wei.(2024).Autonomous Earthquake Location via Deep Reinforcement Learning.SEISMOLOGICAL RESEARCH LETTERS,95(1).
MLA	Kuang, Wenhuan,et al."Autonomous Earthquake Location via Deep Reinforcement Learning".SEISMOLOGICAL RESEARCH LETTERS 95.1(2024).