A seismic source characterization model of multi-station based on graph neural network

IF 1.3 4区地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY

Journal of Earth System Science Pub Date : 2024-08-29 DOI:10.1007/s12040-024-02395-z

Hongbin Qiu, Yongsheng Ma, Yong Lu, Gaochuan Liu, Yongming Huang

引用次数: 0

Abstract

Seismic source characterization is a crucial part of earthquake early warning. With the increasing seismic stations and collected data, some deep learning methods are gradually introduced and perform well in earthquake magnitude evaluation and localization. However, how to handle the sparse and non-European multi-stations is still a problem in earthquake multi-station models. This paper designs a multi-station model based on a graph neural network to accomplish seismic source characterization. The model applies the methods of graph theory to represent earthquake data as graph structure and innovatively adds the earthquake phase picks into the edges of the graph. This method mines the potential information among multi-stations effectively. The proposed methods improve the predicting precision and perform better in real-time performance than the compared models.

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基于图神经网络的多台站震源特征模型

震源特征描述是地震预警的重要组成部分。随着地震台站和采集数据的增加，一些深度学习方法逐渐被引入，并在震级评估和定位方面表现出色。然而，如何处理稀疏和非欧洲多台站仍是地震多台站模型中的一个难题。本文设计了一种基于图神经网络的多台站模型来完成震源表征。该模型运用图论的方法将地震数据表示为图结构，并创新性地在图的边中加入了地震相位选取。该方法有效地挖掘了多台站之间的潜在信息。与同类模型相比，所提出的方法提高了预测精度和实时性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Earth System Science Earth and Planetary Sciences-General Earth and Planetary Sciences

CiteScore

3.20

自引率

5.30%

发文量

226

期刊介绍： The Journal of Earth System Science, an International Journal, was earlier a part of the Proceedings of the Indian Academy of Sciences – Section A begun in 1934, and later split in 1978 into theme journals. This journal was published as Proceedings – Earth and Planetary Sciences since 1978, and in 2005 was renamed ‘Journal of Earth System Science’. The journal is highly inter-disciplinary and publishes scholarly research – new data, ideas, and conceptual advances – in Earth System Science. The focus is on the evolution of the Earth as a system: manuscripts describing changes of anthropogenic origin in a limited region are not considered unless they go beyond describing the changes to include an analysis of earth-system processes. The journal''s scope includes the solid earth (geosphere), the atmosphere, the hydrosphere (including cryosphere), and the biosphere; it also addresses related aspects of planetary and space sciences. Contributions pertaining to the Indian sub- continent and the surrounding Indian-Ocean region are particularly welcome. Given that a large number of manuscripts report either observations or model results for a limited domain, manuscripts intended for publication in JESS are expected to fulfill at least one of the following three criteria. The data should be of relevance and should be of statistically significant size and from a region from where such data are sparse. If the data are from a well-sampled region, the data size should be considerable and advance our knowledge of the region. A model study is carried out to explain observations reported either in the same manuscript or in the literature. The analysis, whether of data or with models, is novel and the inferences advance the current knowledge.