Machine Learning in Earthquake Seismology

IF 11.3 1区 地球科学 Q1 ASTRONOMY & ASTROPHYSICS
S. Mousavi, G. Beroza
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引用次数: 13

Abstract

Machine learning (ML) is a collection of methods used to develop understanding and predictive capability by learning relationships embedded in data. ML methods are becoming the dominant approaches for many tasks in seismology. ML and data mining techniques can significantly improve our capability for seismic data processing. In this review we provide a comprehensive overview of ML applications in earthquake seismology, discuss progress and challenges, and offer suggestions for future work. ▪ Conceptual, algorithmic, and computational advances have enabled rapid progress in the development of machine learning approaches to earthquake seismology. ▪ The impact of that progress is most clearly evident in earthquake monitoring and is leading to a new generation of much more comprehensive earthquake catalogs. ▪ Application of unsupervised approaches for exploratory analysis of these high-dimensional catalogs may reveal new understanding of seismicity. ▪ Machine learning methods are proving to be effective across a broad range of other seismological tasks, but systematic benchmarking through open source frameworks and benchmark data sets are important to ensure continuing progress. Expected final online publication date for the Annual Review of Earth and Planetary Sciences, Volume 51 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
地震学中的机器学习
机器学习(ML)是通过学习嵌入在数据中的关系来开发理解和预测能力的方法集合。机器学习方法正在成为地震学中许多任务的主导方法。ML和数据挖掘技术可以显著提高我们处理地震数据的能力。本文综述了机器学习在地震地震学中的应用,讨论了进展和挑战,并对今后的工作提出了建议。▪概念、算法和计算方面的进步使地震地震学机器学习方法的发展取得了快速进展。这一进展的影响在地震监测方面最为明显,并正在导致新一代更加全面的地震目录的产生。▪应用无监督方法对这些高维目录进行探索性分析,可能会揭示对地震活动性的新认识。机器学习方法已被证明在广泛的其他地震任务中是有效的,但通过开源框架和基准数据集进行系统基准测试对于确保持续进展至关重要。《地球与行星科学年鉴》第51卷的最终在线出版日期预计为2023年5月。修订后的估计数请参阅http://www.annualreviews.org/page/journal/pubdates。
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
Annual Review of Earth and Planetary Sciences
Annual Review of Earth and Planetary Sciences 地学天文-地球科学综合
CiteScore
25.10
自引率
0.00%
发文量
25
期刊介绍: Since its establishment in 1973, the Annual Review of Earth and Planetary Sciences has been dedicated to providing comprehensive coverage of advancements in the field. This esteemed publication examines various aspects of earth and planetary sciences, encompassing climate, environment, geological hazards, planet formation, and the evolution of life. To ensure wider accessibility, the latest volume of the journal has transitioned from a gated model to open access through the Subscribe to Open program by Annual Reviews. Consequently, all articles published in this volume are now available under the Creative Commons Attribution (CC BY) license.
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