MACHINE LEARNING FOR INTELLIGENT PATTERN RECOGNITION METHODS FOR SEISMIC SAFETY (using earthquake swarms as an example)

Year 2025, Volume: 27 Issue: 1, 3 - 9, 30.05.2025

Abdulaziz Abdullaev Yekaterina Lyutikova Irina Litovchenko

https://doi.org/10.59849/2219-6641.2025.1.3

Abstract

The paper presents one of the modern and relevant approaches to using Artificial Intelligence in machine learning, namely, the pattern recognition method. It is one of the powerful tools for intelligent analysis of large volumes of data. Today, there are a huge number of recognition algorithms and technologies for their implementation, including in the processing of seismic data, the use of clustering methods and event recognition in seismology. Such events include weak seismicity (earthquake swarms) in any seismically active region. This approach carries a promising method for representing seismic events in real time, and their visualization occurs directly during the continuous flow of seismic events. To ensure seismic safety of the region in a timely manner, it is necessary to use modernized methods and means of processing large volumes of data. Including the method of cluster analysis of events in the form of pattern recognition, swarms of weak earthquakes. Keywords: Machine learning, Artificial Intelligence (AI), intelligent methods, pattern recognition, seismicity, earthquakes, earthquake swarm, seismic safety

Keywords

Machine learning , Artificial Intelligence (AI) , intelligent methods , pattern recognition , seismicity , earthquakes , earthquake swarm , seismic safety

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