GSTDTAP  > 气候变化
DOI10.1029/2019GL085976
A Machine-Learning Approach for Earthquake Magnitude Estimation
Mousavi, S. Mostafa; Beroza, Gregory C.
2020-01-16
发表期刊GEOPHYSICAL RESEARCH LETTERS
ISSN0094-8276
EISSN1944-8007
出版年2020
卷号47期号:1
文章类型Article
语种英语
国家USA
英文摘要

In this study, we present a fast and reliable method for end-to-end estimation of earthquake magnitude from raw waveforms recorded at single stations. We design a regressor (MagNet) composed of convolutional and recurrent neural networks that is not sensitive to the data normalization, hence waveform amplitude information can be utilized during the training. The network can learn distance-dependent and site-dependent functions directly from the training data. Our model can predict local magnitudes with an average error close to zero and standard deviation of similar to 0.2 based on single-station waveforms without instrument response correction. We test the network for both local and duration magnitude scales and show a station-based learning can be an effective approach for improving the performance. The proposed approach has a variety of potential applications from routine earthquake monitoring to early warning systems.


领域气候变化
收录类别SCI-E
WOS记录号WOS:000513983400032
WOS关键词QUANTIFICATION ; SCALE ; NOISE ; DEEP
WOS类目Geosciences, Multidisciplinary
WOS研究方向Geology
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/279496
专题气候变化
作者单位Stanford Univ, Dept Geophys, Stanford, CA 94305 USA
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GB/T 7714
Mousavi, S. Mostafa,Beroza, Gregory C.. A Machine-Learning Approach for Earthquake Magnitude Estimation[J]. GEOPHYSICAL RESEARCH LETTERS,2020,47(1).
APA Mousavi, S. Mostafa,&Beroza, Gregory C..(2020).A Machine-Learning Approach for Earthquake Magnitude Estimation.GEOPHYSICAL RESEARCH LETTERS,47(1).
MLA Mousavi, S. Mostafa,et al."A Machine-Learning Approach for Earthquake Magnitude Estimation".GEOPHYSICAL RESEARCH LETTERS 47.1(2020).
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