Neural network models of local time curves of seismic waves
To generalize the problem of the travel time assessment the artificial neuron networks are used. This approach makes possible to build the nonlinear model of seismic wave phase propagation as a function of several arguments: source depth, magnitude, back azimuth and epicenter distance. The 3D travel...
Збережено в:
| Дата: | 2011 |
|---|---|
| Автори: | , , |
| Формат: | Стаття |
| Мова: | Російська |
| Опубліковано: |
S. Subbotin Institute of Geophysics of the NAS of Ukraine
2011
|
| Онлайн доступ: | https://journals.uran.ua/geofizicheskiy/article/view/116802 |
| Теги: |
Додати тег
Немає тегів, Будьте першим, хто поставить тег для цього запису!
|
| Назва журналу: | Geofizicheskiy Zhurnal |
Репозитарії
Geofizicheskiy Zhurnal| _version_ | 1856543305262694400 |
|---|---|
| author | Lazarenko, M. A. Gerasimenko, O. A. Ostapchuk, N. N. |
| author_facet | Lazarenko, M. A. Gerasimenko, O. A. Ostapchuk, N. N. |
| author_sort | Lazarenko, M. A. |
| baseUrl_str | |
| collection | OJS |
| datestamp_date | 2020-10-07T11:02:57Z |
| description | To generalize the problem of the travel time assessment the artificial neuron networks are used. This approach makes possible to build the nonlinear model of seismic wave phase propagation as a function of several arguments: source depth, magnitude, back azimuth and epicenter distance. The 3D travel time curves for three Ukrainian seismic stations are presented together with the deviation from global travel time data. |
| first_indexed | 2025-07-17T11:08:00Z |
| format | Article |
| id | journalsuranua-geofizicheskiy-article-116802 |
| institution | Geofizicheskiy Zhurnal |
| language | Russian |
| last_indexed | 2025-07-17T11:08:00Z |
| publishDate | 2011 |
| publisher | S. Subbotin Institute of Geophysics of the NAS of Ukraine |
| record_format | ojs |
| spelling | journalsuranua-geofizicheskiy-article-1168022020-10-07T11:02:57Z Neural network models of local time curves of seismic waves Lazarenko, M. A. Gerasimenko, O. A. Ostapchuk, N. N. To generalize the problem of the travel time assessment the artificial neuron networks are used. This approach makes possible to build the nonlinear model of seismic wave phase propagation as a function of several arguments: source depth, magnitude, back azimuth and epicenter distance. The 3D travel time curves for three Ukrainian seismic stations are presented together with the deviation from global travel time data. S. Subbotin Institute of Geophysics of the NAS of Ukraine 2011-12-01 Article Article application/pdf https://journals.uran.ua/geofizicheskiy/article/view/116802 10.24028/gzh.0203-3100.v33i6.2011.116802 Geofizicheskiy Zhurnal; Vol. 33 No. 6 (2011); 157-160 Геофизический журнал; Том 33 № 6 (2011); 157-160 Геофізичний журнал; Том 33 № 6 (2011); 157-160 2524-1052 0203-3100 ru https://journals.uran.ua/geofizicheskiy/article/view/116802/110862 Copyright (c) 2020 Geofizicheskiy Zhurnal https://creativecommons.org/licenses/by/4.0 |
| spellingShingle | Lazarenko, M. A. Gerasimenko, O. A. Ostapchuk, N. N. Neural network models of local time curves of seismic waves |
| title | Neural network models of local time curves of seismic waves |
| title_full | Neural network models of local time curves of seismic waves |
| title_fullStr | Neural network models of local time curves of seismic waves |
| title_full_unstemmed | Neural network models of local time curves of seismic waves |
| title_short | Neural network models of local time curves of seismic waves |
| title_sort | neural network models of local time curves of seismic waves |
| url | https://journals.uran.ua/geofizicheskiy/article/view/116802 |
| work_keys_str_mv | AT lazarenkoma neuralnetworkmodelsoflocaltimecurvesofseismicwaves AT gerasimenkooa neuralnetworkmodelsoflocaltimecurvesofseismicwaves AT ostapchuknn neuralnetworkmodelsoflocaltimecurvesofseismicwaves |