Analysis of earthquake hypocenter characteristics using chaos game representation.

IF 2.1 3区地球科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computational Geosciences Pub Date : 2023-01-01 DOI:10.1007/s10596-022-10187-x

Cyril Shaju, Kamal

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引用次数: 1

Abstract

This paper proposes a new method to approach earthquake hypocenter studies based on Chaos Game Representation (CGR), a method initially used for making fractal structures and applied for studying DNA sequences. Applying the CGR method, this study aims at checking whether any relation exists between earthquakes occurring in different depth ranges in a seismically active area. For this purpose, the seismically active areas around the Indian tectonic plate were used. The CGR images gave characteristic patterns, implying that the occurrence of earthquakes in some specific depth range combinations showed higher preference. Statistical data on the frequency of different depth range combinations were derived from these plots. We put forward a mathematical value which we call proximity index, to compare the similarity between two different CGR plots. Proximity index values were used to compare the similarity in seismic activity in two different zones by comparing their respective CGR plots.

Supplementary information: The online version contains supplementary material available at 10.1007/s10596-022-10187-x.

查看原文本刊更多论文

用混沌博弈表示分析震源特征。

本文提出了一种基于混沌博弈表示(Chaos Game Representation, CGR)的地震震源研究新方法。混沌博弈表示最初用于构造分形结构，并应用于DNA序列的研究。本研究采用CGR方法，旨在检验地震活跃区内不同深度范围的地震之间是否存在联系。为此，研究人员利用了印度构造板块周围的地震活跃区域。CGR图像给出了特征模式，表明地震发生在某些特定深度范围组合中表现出较高的偏好。从这些图中得到了不同深度范围组合频率的统计数据。我们提出了一个数学值，我们称之为接近指数，以比较两个不同的CGR图之间的相似度。利用邻近指数值比较两个不同带的地震活动的相似性，通过比较它们各自的CGR图。补充信息:在线版本包含补充资料，可在10.1007/s10596-022-10187-x获得。

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

Computational Geosciences 地学-地球科学综合

CiteScore

6.10

自引率

4.00%

发文量

审稿时长

6-12 weeks

期刊介绍： Computational Geosciences publishes high quality papers on mathematical modeling, simulation, numerical analysis, and other computational aspects of the geosciences. In particular the journal is focused on advanced numerical methods for the simulation of subsurface flow and transport, and associated aspects such as discretization, gridding, upscaling, optimization, data assimilation, uncertainty assessment, and high performance parallel and grid computing. Papers treating similar topics but with applications to other fields in the geosciences, such as geomechanics, geophysics, oceanography, or meteorology, will also be considered. The journal provides a platform for interaction and multidisciplinary collaboration among diverse scientific groups, from both academia and industry, which share an interest in developing mathematical models and efficient algorithms for solving them, such as mathematicians, engineers, chemists, physicists, and geoscientists.