中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
MagInfoNet: Magnitude Estimation Using Seismic Information Augmentation and Graph Transformer

文献类型:期刊论文

作者Chen, Ziwei1; Wang, Zhiguo1; Wu, Shaojiang2; Wang, Yibo2; Gao, Jinghuai1
刊名EARTH AND SPACE SCIENCE
出版日期2022-12-01
卷号9期号:12页码:15
关键词magnitude estimation seismic signal arrival time travel time residual neural network graph neural network
DOI10.1029/2022EA002580
英文摘要In this study, we propose a reliable data-driven tool, MagInfoNet, to enhance the accuracy of magnitude estimation. Its architecture was assembled using the Pre-Inform and Mag-Pred modules to replace and update the key functions of traditional seismic analysis workflows. The Pre-Inform module with the residual network was used for data pretreatment by combining the intrinsic characteristics of seismic signals with the potential features of the arrival and travel times. Meanwhile, using a graph transformer with an improved cyclic graph, the Mag-Pred module was used to calculate magnitudes by the preprocessed information and the autocorrelation of seismic time series. Training and testing data were randomly selected from the Stanford Earthquake Data Set. The results show that the estimation accuracy, generalization, and robustness of the proposed MagInfoNet are better than those of three machine learning models. Besides, MagInfoNet can perform better for those samples with larger epicentral distances, enhancing the monitoring capacity of existing system for earthquake events in remote areas. Finally, we discuss the interpretability of the explainable MagInfoNet to verify the role of advanced neural network modules.
WOS关键词NEURAL-NETWORKS ; TIME-SERIES ; EARTHQUAKE ; FRAMEWORK
资助项目National Natural Science Foundation of China[41974137]
WOS研究方向Astronomy & Astrophysics ; Geology
语种英语
WOS记录号WOS:000924585900001
出版者AMER GEOPHYSICAL UNION
资助机构National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China
源URL[http://ir.iggcas.ac.cn/handle/132A11/106794]  
专题地质与地球物理研究所_中国科学院油气资源研究重点实验室
通讯作者Wang, Zhiguo
作者单位1.Xi An Jiao Tong Univ, Sch Math & Stat, Xian, Peoples R China
2.Chinese Acad Sci, Key Lab Petr Resource Res, Inst Geol & Geophys, Beijing, Peoples R China
推荐引用方式
GB/T 7714
Chen, Ziwei,Wang, Zhiguo,Wu, Shaojiang,et al. MagInfoNet: Magnitude Estimation Using Seismic Information Augmentation and Graph Transformer[J]. EARTH AND SPACE SCIENCE,2022,9(12):15.
APA Chen, Ziwei,Wang, Zhiguo,Wu, Shaojiang,Wang, Yibo,&Gao, Jinghuai.(2022).MagInfoNet: Magnitude Estimation Using Seismic Information Augmentation and Graph Transformer.EARTH AND SPACE SCIENCE,9(12),15.
MLA Chen, Ziwei,et al."MagInfoNet: Magnitude Estimation Using Seismic Information Augmentation and Graph Transformer".EARTH AND SPACE SCIENCE 9.12(2022):15.

入库方式: OAI收割

来源:地质与地球物理研究所

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