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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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 |
_version_ |
1772817986172747776 |