The Behavior of VLF/LF Variations Associated with Geomagnetic Activity, Earthquakes, and the Quiet Condition Using a Neural Network Approach
The neural network approach is proposed for studying very-low- and low-frequency (VLF and LF) subionospheric radio wave variations in the time vicinities of magnetic storms and earthquakes, with the purpose of recognizing anomalies of different types. We also examined the days with quiet geomagnetic...
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ftpubmed:oai:pubmedcentral.nih.gov:7513217 2023-05-15T16:59:11+02:00 The Behavior of VLF/LF Variations Associated with Geomagnetic Activity, Earthquakes, and the Quiet Condition Using a Neural Network Approach Popova, Irina Rozhnoi, Alexandr Solovieva, Maria Chebrov, Danila Hayakawa, Masashi 2018-09-11 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513217/ https://doi.org/10.3390/e20090691 en eng MDPI http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513217/ http://dx.doi.org/10.3390/e20090691 © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). CC-BY Entropy (Basel) Article Text 2018 ftpubmed https://doi.org/10.3390/e20090691 2020-11-15T01:21:23Z The neural network approach is proposed for studying very-low- and low-frequency (VLF and LF) subionospheric radio wave variations in the time vicinities of magnetic storms and earthquakes, with the purpose of recognizing anomalies of different types. We also examined the days with quiet geomagnetic conditions in the absence of seismic activity, in order to distinguish between the disturbed signals and the quiet ones. To this end, we trained the neural network (NN) on the examples of the representative database. The database included both the VLF/LF data that was measured during four-year monitoring at the station in Petropavlovsk-Kamchatsky, and the parameters of seismicity in the Kuril-Kamchatka and Japan regions. It was shown that the neural network can distinguish between the disturbed and undisturbed signals. Furthermore, the prognostic behavior of the VLF/LF variations indicative of magnetic and seismic activity has a different appearance in the time vicinity of the earthquakes and magnetic storms. Text Kamchatka PubMed Central (PMC) Petropavlovsk ENVELOPE(158.626,158.626,53.067,53.067) Petropavlovsk-Kamchatsky ENVELOPE(158.651,158.651,53.044,53.044) Entropy 20 9 691 |
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Article Popova, Irina Rozhnoi, Alexandr Solovieva, Maria Chebrov, Danila Hayakawa, Masashi The Behavior of VLF/LF Variations Associated with Geomagnetic Activity, Earthquakes, and the Quiet Condition Using a Neural Network Approach |
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Article |
description |
The neural network approach is proposed for studying very-low- and low-frequency (VLF and LF) subionospheric radio wave variations in the time vicinities of magnetic storms and earthquakes, with the purpose of recognizing anomalies of different types. We also examined the days with quiet geomagnetic conditions in the absence of seismic activity, in order to distinguish between the disturbed signals and the quiet ones. To this end, we trained the neural network (NN) on the examples of the representative database. The database included both the VLF/LF data that was measured during four-year monitoring at the station in Petropavlovsk-Kamchatsky, and the parameters of seismicity in the Kuril-Kamchatka and Japan regions. It was shown that the neural network can distinguish between the disturbed and undisturbed signals. Furthermore, the prognostic behavior of the VLF/LF variations indicative of magnetic and seismic activity has a different appearance in the time vicinity of the earthquakes and magnetic storms. |
format |
Text |
author |
Popova, Irina Rozhnoi, Alexandr Solovieva, Maria Chebrov, Danila Hayakawa, Masashi |
author_facet |
Popova, Irina Rozhnoi, Alexandr Solovieva, Maria Chebrov, Danila Hayakawa, Masashi |
author_sort |
Popova, Irina |
title |
The Behavior of VLF/LF Variations Associated with Geomagnetic Activity, Earthquakes, and the Quiet Condition Using a Neural Network Approach |
title_short |
The Behavior of VLF/LF Variations Associated with Geomagnetic Activity, Earthquakes, and the Quiet Condition Using a Neural Network Approach |
title_full |
The Behavior of VLF/LF Variations Associated with Geomagnetic Activity, Earthquakes, and the Quiet Condition Using a Neural Network Approach |
title_fullStr |
The Behavior of VLF/LF Variations Associated with Geomagnetic Activity, Earthquakes, and the Quiet Condition Using a Neural Network Approach |
title_full_unstemmed |
The Behavior of VLF/LF Variations Associated with Geomagnetic Activity, Earthquakes, and the Quiet Condition Using a Neural Network Approach |
title_sort |
behavior of vlf/lf variations associated with geomagnetic activity, earthquakes, and the quiet condition using a neural network approach |
publisher |
MDPI |
publishDate |
2018 |
url |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513217/ https://doi.org/10.3390/e20090691 |
long_lat |
ENVELOPE(158.626,158.626,53.067,53.067) ENVELOPE(158.651,158.651,53.044,53.044) |
geographic |
Petropavlovsk Petropavlovsk-Kamchatsky |
geographic_facet |
Petropavlovsk Petropavlovsk-Kamchatsky |
genre |
Kamchatka |
genre_facet |
Kamchatka |
op_source |
Entropy (Basel) |
op_relation |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513217/ http://dx.doi.org/10.3390/e20090691 |
op_rights |
© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.3390/e20090691 |
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