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Identification and spatio-temporal analysis of earthquake clusters using SOM–DBSCAN model

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Abstract

Seismic catalogs are vital to understanding and analyzing the progress of active fault systems. The background seismicity rate in a seismic catalog, strongly associated with stressing rate, is the critical parameter in seismic hazard analysis. Estimating background seismicity is a complex task due to the high correlation with aftershock sequences which may dominate the background seismicity rate. In this paper, identification of the significant earthquake aftershocks and independent background events is performed using a two-stage clustering approach. It works in two phases: Self-Organized Map and Density-based Temporal Clustering. The event’s location and depth information in the earthquake catalog is used to identify the major hot spots (SOM prototypes) in the region (Spatial domain). Later, density-based temporal clustering is applied to decipher the neighborhood events of each SOM prototype. The proposed two-level clustering approach performs effective spatio-temporal analysis and identifies the aftershock clusters and background. The experimental study is carried out on the prominent earthquake catalogs of Taiwan, Afghanistan, California, the Himalayas, Indonesia, Chile, and Japan. The statistical parameters: Coefficient of Variation (time-domain) and m-Morisita index (spatial domain) justify and validate the accuracy of the presented approach. The proposed model is compared with benchmark de-clustering algorithms for mainshock and background detection.

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Data availability

The datasets (seismic catalogs) analysed during the current study are available at the official website of United State Geological Survey [https://earthquake.usgs.gov/earthquakes/search/].

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Acknowledgements

This research work is funded by Ministry of Electronics and Information and IT under Visvesvaraya PhD Scheme with Grant Number-1000110674 and unique awardee number MEITY-PHD-2952.

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Author notes

  1. Rahul Kumar Vijay and Satyasai Jagannath Nanda have contributed equally to this work.

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Malaviya National Institute of Technology Jaipur, Jaipur, Rajasthan, 302017, India

    Ashish Sharma & Satyasai Jagannath Nanda

  2. Department of Computer Science, Banasthali Vidyapith, Tonk, Rajasthan, 304022, India

    Rahul Kumar Vijay

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  1. Ashish Sharma
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Correspondence to Ashish Sharma.

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Sharma, A., Vijay, R.K. & Nanda, S.J. Identification and spatio-temporal analysis of earthquake clusters using SOM–DBSCAN model. Neural Comput & Applic 35, 8081–8108 (2023). https://doi.org/10.1007/s00521-022-08085-5

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