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The Role of Machine Learning in Earthquake Seismology: A Review

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Abstract

This comprehensive survey addresses the notable yet relatively uncharted territory of machine learning (ML) applications within the realm of earthquake engineering. While previous reviews have touched on ML’s involvement, this work strives to fill a gap by providing an extensive analysis of the extent to which ML has permeated earthquake engineering. It delves into how ML is facilitating and propelling research endeavors while aiding decision-makers in mitigating the repercussions of seismic hazards on civil structures. Earthquake engineering, an interdisciplinary field, encompasses the assessment of seismic hazards, characterization of site-specific effects, analysis of structural responses, evaluation of seismic risk and vulnerability, and examination of seismic protection measures. ML algorithms find application in a multitude of scenarios within each of these subfields, contributing to advancements in earthquake engineering research and practice.

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  1. Department of Civil Engineering, P. R. Pote Patil College of Engineering and Management, Amravati, Maharashtra, India

    Anup Chitkeshwar

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Chitkeshwar, A. The Role of Machine Learning in Earthquake Seismology: A Review. Arch Computat Methods Eng (2024). https://doi.org/10.1007/s11831-024-10099-2

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