Open AccessDetection of records of weak local earthquakes using neural networks
Author(s) -
N. A. Ul'yanov,
Sergey Yaskevich,
П. А. Дергач,
A. V. YablokovAV
Publication year - 2022
Publication title -
geofizičeskie tehnologii
Language(s) - English
Resource type - Journals
ISSN - 2619-1563
DOI - 10.18303/2619-1563-2021-2-13
Subject(s) - seismogram , event (particle physics) , seismology , noise (video) , computer science , energy (signal processing) , amplitude , artificial neural network , algorithm , geology , data mining , artificial intelligence , mathematics , statistics , physics , quantum mechanics , image (mathematics)
Manual processing of large volumes of continuous observations produced by local seismic networks takes a lot of time, therefore, to solve this problem, automatic algorithms for detecting seismic events are used. Deterministic methods for solving the problem of detection, which do an excellent job of detecting intensive earthquakes, face critical problems when detecting weak seismic events (earthquakes). They are based on principles based on the calculation of energy, which causes multiple errors in detection: weak seismic events may not be detected, and high-amplitude noise may be mistakenly detected as an event. In our work, we propose a detection method capable of surpassing deterministic methods in detecting events on seismograms, successfully detecting a similar or more events with fewer false detections.