基于ETAS.inlabru的2022年芦山M_(s)6.1地震序列建模与分析  

Study on the Modeling and Analysis of the 2022 Lushan M_(s)6.1 Earthquake Sequence Based on ETAS.inlabru

作　　者：任馨怡 Ren Xinyi(School of Mathematics,University of Edinburgh,Edinburgh EH88FH,UK)

机构地区：[1]爱丁堡大学数学学院,英国爱丁堡EH88FH

出　　处：《中阿科技论坛(中英文)》2025年第4期82-86,共5页China-Arab States Science and Technology Forum

摘　　要：传染型余震序列(ETAS)模型是地震序列分析与预测的重要工具,近年来在地震学研究中得到了广泛应用。随着贝叶斯方法在参数估计和不确定性量化方面的优势逐渐凸显,其在地震建模领域的应用也日益受到关注。基于集成嵌套拉普拉斯近似(INLA)的ETAS建模方法,为传统ETAS模型分析提供了新的理论与计算框架。文章利用R语言中的ETAS.inlabru包,对2022年6月1日芦山M_(S)6.1级地震的余震序列进行了建模分析。通过对模型参数后验分布的分析以及余震发生数量的预测,探讨了该方法在真实地震序列预测中的应用潜力。此外,文章还采用N-test检验方法对预测效果进行了量化评估,以验证模型的可靠性。研究结果表明,基于ETAS.inlabru的建模方法能够有效捕捉地震序列的时空特征,并为余震预测提供科学依据,为地震预测的理论与实践提供了新的思路。ETAS model is an important tool for earthquake sequence analysis and prediction,and has been widely used in seismological research in recent years.As the advantages of Bayesian methods in parameter estimation and uncertainty quantification have been highlighted,their application in earthquake modeling is also receiving increasing attention.The ETAS modeling based on integrated nested Laplace approximation(INLA)provides a new theoretical and computational framework for traditional ETAS model analysis.In this context,the article uses the ETAS.inlabru package in R language to model and analyze the aftershock sequence of the M_(s) 6.1 Lushan earthquake on June 1,2022.By analyzing the posterior distribution of model parameters and predicting the number of aftershocks,the potential of this method in predicting earthquake sequences was explored.In addition,N-test was employed to quantitatively evaluate the prediction,in order to verify the reliability of the model.The research findings indicate that the modeling method can effectively capture the spatial-temporal characteristics of earthquake sequences and provide scientific basis for aftershock prediction,providing new ideas for the theory and practice of earthquake prediction.

关 键 词：地震序列 ETAS模型 贝叶斯分析 统计检验 

分 类 号：G304[文化科学]