Development of events detector for monitoring cryoseisms in upper soils

Abstract In this article, we describe the first results of the development of the seismic events detector with an artificial neural network (ANN) based identification. Such a detector is necessary for studying seismic events induced by soil freezing that can be hazardous for urban and mining infrast...

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Main Authors: Afonin, N. (Nikita), Kozlovskaya, E. (Elena)
Format: Article in Journal/Newspaper
Language:English
Published: Geofysiikan seura 2019
Subjects:
Online Access:http://urn.fi/urn:nbn:fi-fe202003208608
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spelling ftunivoulu:oai:oulu.fi:nbnfi-fe202003208608 2023-07-30T04:05:49+02:00 Development of events detector for monitoring cryoseisms in upper soils Afonin, N. (Nikita) Kozlovskaya, E. (Elena) 2019 application/pdf http://urn.fi/urn:nbn:fi-fe202003208608 eng eng Geofysiikan seura info:eu-repo/semantics/openAccess Julkaisu vapaasti saatavilla Geofysiikan seuran sivustolta https://www.geofysiikanseura.fi info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 2019 ftunivoulu 2023-07-08T19:56:32Z Abstract In this article, we describe the first results of the development of the seismic events detector with an artificial neural network (ANN) based identification. Such a detector is necessary for studying seismic events induced by soil freezing that can be hazardous for urban and mining infrastructures. We used the data of about 300 such seismic events recorded by seismic station OUL of Northern Finland Seismological Network for testing the detector and neural network learning. We processed about two months of continuous data and found out, that in some cases the number of detected and identified seismic events per day depends on air temperature variation. Article in Journal/Newspaper Northern Finland Jultika - University of Oulu repository
institution Open Polar
collection Jultika - University of Oulu repository
op_collection_id ftunivoulu
language English
description Abstract In this article, we describe the first results of the development of the seismic events detector with an artificial neural network (ANN) based identification. Such a detector is necessary for studying seismic events induced by soil freezing that can be hazardous for urban and mining infrastructures. We used the data of about 300 such seismic events recorded by seismic station OUL of Northern Finland Seismological Network for testing the detector and neural network learning. We processed about two months of continuous data and found out, that in some cases the number of detected and identified seismic events per day depends on air temperature variation.
format Article in Journal/Newspaper
author Afonin, N. (Nikita)
Kozlovskaya, E. (Elena)
spellingShingle Afonin, N. (Nikita)
Kozlovskaya, E. (Elena)
Development of events detector for monitoring cryoseisms in upper soils
author_facet Afonin, N. (Nikita)
Kozlovskaya, E. (Elena)
author_sort Afonin, N. (Nikita)
title Development of events detector for monitoring cryoseisms in upper soils
title_short Development of events detector for monitoring cryoseisms in upper soils
title_full Development of events detector for monitoring cryoseisms in upper soils
title_fullStr Development of events detector for monitoring cryoseisms in upper soils
title_full_unstemmed Development of events detector for monitoring cryoseisms in upper soils
title_sort development of events detector for monitoring cryoseisms in upper soils
publisher Geofysiikan seura
publishDate 2019
url http://urn.fi/urn:nbn:fi-fe202003208608
genre Northern Finland
genre_facet Northern Finland
op_rights info:eu-repo/semantics/openAccess
Julkaisu vapaasti saatavilla Geofysiikan seuran sivustolta https://www.geofysiikanseura.fi
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