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ИСПОЛЬЗОВАНИЕ ИСКУССТВЕННЫХ НЕЙРОННЫХ СЕТЕЙ
В КЛАССИФИКАЦИИ ЗАШУМЛЕННЫХ
СЕЙСМИЧЕСКИХ СИГНАЛОВ
Институт теории прогноза землетрясений и математической геофизики РАН
Журнал: Сейсмические приборы
Том: 52
Номер: 2
Год: 2016
Страницы: 46-64
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КИСЛОВ К.В., ГРАВИРОВ В.В. ИСПОЛЬЗОВАНИЕ ИСКУССТВЕННЫХ НЕЙРОННЫХ СЕТЕЙ
В КЛАССИФИКАЦИИ ЗАШУМЛЕННЫХ
СЕЙСМИЧЕСКИХ СИГНАЛОВ // Сейсмические приборы. 2016. Т. 52. № 2. С. 46-64.
@article{КИСЛОВИСПОЛЬЗОВАНИЕ2016,
author = "КИСЛОВ, К. В. and ГРАВИРОВ, В. В.",
title = "ИСПОЛЬЗОВАНИЕ ИСКУССТВЕННЫХ НЕЙРОННЫХ СЕТЕЙ
В КЛАССИФИКАЦИИ ЗАШУМЛЕННЫХ
СЕЙСМИЧЕСКИХ СИГНАЛОВ",
journal = "Сейсмические приборы",
year = 2016,
volume = "52",
number = "2",
pages = "46-64",
doi = "",
language = "Russian"
}
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Ключевые слова: классификация сигналов, детектирование сейсмических сигналов, искусственные нейронные сети, рутинная обработка
Аннотация: ИСПОЛЬЗОВАНИЕ ИСКУССТВЕННЫХ НЕЙРОННЫХ СЕТЕЙ
В КЛАССИФИКАЦИИ ЗАШУМЛЕННЫХ
СЕЙСМИЧЕСКИХ СИГНАЛОВ
Список литературы: Баранов С.В. Применение нейронных сетей к уменьшению ложных срабатываний при автоматическом детектировании сейсмических сигналов / Тезисы докладов Второй региональной научно-технической конференции Проблемы комплексного геофизического мониторинга Дальнего Востока России. Петропавловск-Камчатский: ГС РАН, 2009. C.108-190.
Гравиров В.В., Кислов К.В., Винберг Ф.Э. Выделение информативного сигнала из нестационарных сильнозашумленных сейсмических данных с использованием нейросетевых классификаторов // Промышленные АСУ и контроллеры. 2012. № 12. С.45-49.
Кислов К.В., Гравиров В.В. Распознавание вступления землетрясения на фоне техногенных шумов // Сейсмические приборы. 2010. Т. 46, № 2. С.26-46.
Назимов А.И. Адаптивные методы анализа зашумленных нестационарных сигналов на основе вейвлет-преобразования и алгоритма искусственных нейронных сетей: Дис. … канд. физ.-мат. наук. Саратов, 2014.
Самарин А.И. Нейронные сети с преднастройкой // Научная сессия МИФИ-2005. VII Всероссийская научно-техническая конференция Нейроинформатика - 2005: Лекции по нейроинформатике. М.: МИФИ, 2005. C.13-42.
Abu-Elsoud M.A., Abou-Chadi F.E.Z., Amin A.E.M., Mahana M. Classification of seismic events in Suez Gulf area, Egypt using artificial neural network // ICEEE'04: 2004 International Conference on Electrical, Electronic and Computer Engineering. Proceedings, 2004. P.337-340.
Bertsekas D.P., Tsitsiklis J.N. Neuro-Dynamic Programming // Athena Scientific, 1996. 512 p.
Böse M., Wenzel F., Erdik M. PreSEIS: A neural network-based approach to earthquake early warning for finite faults // Bull. Seismol. Soc. Amer. 2008. V. 98, N 1. P.366-382.
Carpenter G.A., Grossberg S. Adaptive resonance theory. Encyclopedia of Machine Learning and Data Mining / Eds. C. Sammut, G. Webb. Berlin: Springer-Verlag, 2014. 18 p. (http://cns.bu.edu/ ~steve/CarpenterGrossbergMachineLearning.pdf).
Cichowicz A. An automatic S-phase picker // Bull. Seismol. Soc. Amer. 1993. V. 83, N 1. P.180-189.
Cybenko G. Approximation by superpositions of a sigmoidal function // Mathematical Control Signals Systems. 1989. N 2. P.303-314.
Del Pezzo E., Esposito A., Giudicepietro F., Marinaro M., Martini M., Scarpetta S. Discrimination of earthquakes and underwater explosions using neural networks // Bull. Seismol. Soc. Amer. 2003. V. 93, N 1. P.215-223.
Dreyfus G. Neural Networks: Methodology and Applications. Springer Science & Business Media, 2005. 498 p.
Essenreiter R., Karrenbach M., Treitel S. Identification and classification of multiple reflections with self-organizing maps // Geophys. Prospect. 2001. V. 49, N 3. P.341-352.
Evans J.R., Allen S.S. A Teleseism-specific detection algorithm for short-period traces // Bull. Seismol. Soc. Amer. 1983. V. 73, N 4. P.1173-1186.
Gentili S., Bragato P. A neural-tree-based system for automatic location of earthquakes in Northeastern Italy // Journal of Seismology. 2006. V. 10, N 1. P.73-89.
Gravirov V.V., Kislov K.V. Development of a hybrid earthquake early warning system based on single sensor technique // NED University Journal of Research. 2012. Thematic Issue on Earthquakes. Karachi, Pakistan. P.1-20. ().
Hecht-Nielsen R. Kolmogorov's mapping neural network existence theorem / IEEE First Annual Int. Conf. on Neural Networks, San Diego. 1987. V. 3. P.11-13.
Kislov K.V., Gravirov V.V. Neural network techniques for earthquake detection in high noise // Электронный журнал Исследовано в России. 2010. 070е. C.837-848. ().
Kislov K.V., Gravirov V.V. Magnitude threshold reducing for a network of close located Mobile stations // Proceedings of the 10th Intl Conf. Problems of Geocosmos (2014, St. Petersburg, Russia) / Eds. V.N. Troyan, N.Yu. Bobrov, A.A. Kosterov, A.A. Samsonov, N.A. Smirnova, T.B. Yanovskaya. St. Petersburg State University, St. Petersburg, Petrodvorets, 2014. P.178-183.
Kislov K.V., Vinberg F.E., Kushnir A.F., Gravirov V.V. Early warning system and man-made noise / Proceedings of the IV International Conference Problems of Cybernetics and Informatics (PCI'2012), Baku, Azerbaijan, 2012. P.52-55. ().
Köhler A., Ohrnberger M., Scherbaum F. Unsupervised pattern recognition in continuous seismic wavefield records using Self-Organizing Maps // Geophysical Journal International. 2010. V. 182, N 3. P.1619-1630.
Kurzon I., Vernon F.L., Rosenberger A., Ben-Zion Y. Real-time automatic detectors of P and S waves using singular value decomposition // Bull. Seismol. Soc. Amer. 2014. V. 104(4). P. 1696-1708.
Kuyuk H.S., Yildirim E., Dogan E., Horasan G. An unsupervised learning algorithm: application to the discrimination of seismic events and quarry blasts in the vicinity of Istanbul // Nat. Hazards Earth Syst. Sci. 2011. V. 11. P.93-100.
Leonard M., Kennett B.L.N. Multi component autoregressive techniques for the analysis of seismograms // Phys. Earth Planet. Int. 1999. V. 113, N 2. P.247-264.
Lin Chu-Chieh J., Pei-Yang Lin, Tao-Ming Chang, Tzu-Kun Lin, Yuan-Tao Weng, Kuo-Chen Chang and Keh-Chyuan Tsai. Development of on-site earthquake early warning system for Taiwan // earthquake research and analysis // New Frontiers in Seismology / Ed. by S. D'Amico. Publisher: InTech, 2012. P.329-358.
Lo J.T., Bassu D. Adaptive multilayer perceptrons with long- and short-term memories // IEEE Transactions On Neural Networks. 2002. V. 13, N 1. P.22-33.
Madureira G., Ruano A.E. A neural network seismic detector // Acta Technica Jaurinensis. 2009. V. 2, N 2. P.159-170.
McEvilly T.V., Majer E.L. ASP: An automated seismic processor for microearthquake networks // Bull. Seismol. Soc. Amer. 1982. V. 72, N 1. P.303-325.
Plešinger A., Rŭžek B., Boušková A. Statistical interpretation of WEBNET seismograms by artificial neural nets // Studia Geophysica et Geodaetica. 2000. V. 44, N 2. P.251-271.
Reading A., Mao W., Gubbins D. Polarization filtering for automatic picking of seismic data and improved converted phase detection // Geophys. J. Int. 2001. V. 147, N 1. P.227-234.
Scarpetta S., Giudicepietro F., Ezin E.C., Petrosino S., Del Pezzo E., Martini M., Marinaro M. Automatic classification of seismic signals at Mt. Vesuvius Volcano, Italy, using neural networks // Bull. Seismol. Soc. Amer. 2005. V. 95, N 1. P.185-196.
Sick B., Guggenmos M., Joswig M. Chances and limits of single-station seismic event clustering by unsupervised pattern recognition // Geophys. J. Int. 2015. V. 201, N 3. P.1801-1813.
Williams R.J., Zipser D. A learning algorithm for continually running fully recurrent neural networks // Neural Computation. 1989. V. 1. P.270-280.
Wiszniowski J., Plesiewicz B.M., Trojanowski J. Application of real time recurrent neural network for detection of small natural earthquakes in Poland // Acta Geophysica. 2014. V. 62, N 3. P.469-485.
Withers M., Aster R., Young C., Beiriger J., Harris M., Moore S., Trujillo J. A comparison of select trigger algorithms for automated global seismic phase and event detection // Bull. Seismol. Soc. Amer. 1998. V. 88, N 1. P.95-106.
Zhang H., Thurber C., Rowe C. Automatic P-wave arrival detection and picking with multiscale wavelet analysis for single-component recording // Bull. Seismol. Soc. Amer. 2003. V. 93, N 5. P.1904-1912.
Гравиров В.В., Кислов К.В., Винберг Ф.Э. Выделение информативного сигнала из нестационарных сильнозашумленных сейсмических данных с использованием нейросетевых классификаторов // Промышленные АСУ и контроллеры. 2012. № 12. С.45-49.
Кислов К.В., Гравиров В.В. Распознавание вступления землетрясения на фоне техногенных шумов // Сейсмические приборы. 2010. Т. 46, № 2. С.26-46.
Назимов А.И. Адаптивные методы анализа зашумленных нестационарных сигналов на основе вейвлет-преобразования и алгоритма искусственных нейронных сетей: Дис. … канд. физ.-мат. наук. Саратов, 2014.
Самарин А.И. Нейронные сети с преднастройкой // Научная сессия МИФИ-2005. VII Всероссийская научно-техническая конференция Нейроинформатика - 2005: Лекции по нейроинформатике. М.: МИФИ, 2005. C.13-42.
Abu-Elsoud M.A., Abou-Chadi F.E.Z., Amin A.E.M., Mahana M. Classification of seismic events in Suez Gulf area, Egypt using artificial neural network // ICEEE'04: 2004 International Conference on Electrical, Electronic and Computer Engineering. Proceedings, 2004. P.337-340.
Bertsekas D.P., Tsitsiklis J.N. Neuro-Dynamic Programming // Athena Scientific, 1996. 512 p.
Böse M., Wenzel F., Erdik M. PreSEIS: A neural network-based approach to earthquake early warning for finite faults // Bull. Seismol. Soc. Amer. 2008. V. 98, N 1. P.366-382.
Carpenter G.A., Grossberg S. Adaptive resonance theory. Encyclopedia of Machine Learning and Data Mining / Eds. C. Sammut, G. Webb. Berlin: Springer-Verlag, 2014. 18 p. (http://cns.bu.edu/ ~steve/CarpenterGrossbergMachineLearning.pdf).
Cichowicz A. An automatic S-phase picker // Bull. Seismol. Soc. Amer. 1993. V. 83, N 1. P.180-189.
Cybenko G. Approximation by superpositions of a sigmoidal function // Mathematical Control Signals Systems. 1989. N 2. P.303-314.
Del Pezzo E., Esposito A., Giudicepietro F., Marinaro M., Martini M., Scarpetta S. Discrimination of earthquakes and underwater explosions using neural networks // Bull. Seismol. Soc. Amer. 2003. V. 93, N 1. P.215-223.
Dreyfus G. Neural Networks: Methodology and Applications. Springer Science & Business Media, 2005. 498 p.
Essenreiter R., Karrenbach M., Treitel S. Identification and classification of multiple reflections with self-organizing maps // Geophys. Prospect. 2001. V. 49, N 3. P.341-352.
Evans J.R., Allen S.S. A Teleseism-specific detection algorithm for short-period traces // Bull. Seismol. Soc. Amer. 1983. V. 73, N 4. P.1173-1186.
Gentili S., Bragato P. A neural-tree-based system for automatic location of earthquakes in Northeastern Italy // Journal of Seismology. 2006. V. 10, N 1. P.73-89.
Gravirov V.V., Kislov K.V. Development of a hybrid earthquake early warning system based on single sensor technique // NED University Journal of Research. 2012. Thematic Issue on Earthquakes. Karachi, Pakistan. P.1-20. (
Hecht-Nielsen R. Kolmogorov's mapping neural network existence theorem / IEEE First Annual Int. Conf. on Neural Networks, San Diego. 1987. V. 3. P.11-13.
Kislov K.V., Gravirov V.V. Neural network techniques for earthquake detection in high noise // Электронный журнал Исследовано в России. 2010. 070е. C.837-848. (
Kislov K.V., Gravirov V.V. Magnitude threshold reducing for a network of close located Mobile stations // Proceedings of the 10th Intl Conf. Problems of Geocosmos (2014, St. Petersburg, Russia) / Eds. V.N. Troyan, N.Yu. Bobrov, A.A. Kosterov, A.A. Samsonov, N.A. Smirnova, T.B. Yanovskaya. St. Petersburg State University, St. Petersburg, Petrodvorets, 2014. P.178-183.
Kislov K.V., Vinberg F.E., Kushnir A.F., Gravirov V.V. Early warning system and man-made noise / Proceedings of the IV International Conference Problems of Cybernetics and Informatics (PCI'2012), Baku, Azerbaijan, 2012. P.52-55. (
Köhler A., Ohrnberger M., Scherbaum F. Unsupervised pattern recognition in continuous seismic wavefield records using Self-Organizing Maps // Geophysical Journal International. 2010. V. 182, N 3. P.1619-1630.
Kurzon I., Vernon F.L., Rosenberger A., Ben-Zion Y. Real-time automatic detectors of P and S waves using singular value decomposition // Bull. Seismol. Soc. Amer. 2014. V. 104(4). P. 1696-1708.
Kuyuk H.S., Yildirim E., Dogan E., Horasan G. An unsupervised learning algorithm: application to the discrimination of seismic events and quarry blasts in the vicinity of Istanbul // Nat. Hazards Earth Syst. Sci. 2011. V. 11. P.93-100.
Leonard M., Kennett B.L.N. Multi component autoregressive techniques for the analysis of seismograms // Phys. Earth Planet. Int. 1999. V. 113, N 2. P.247-264.
Lin Chu-Chieh J., Pei-Yang Lin, Tao-Ming Chang, Tzu-Kun Lin, Yuan-Tao Weng, Kuo-Chen Chang and Keh-Chyuan Tsai. Development of on-site earthquake early warning system for Taiwan // earthquake research and analysis // New Frontiers in Seismology / Ed. by S. D'Amico. Publisher: InTech, 2012. P.329-358.
Lo J.T., Bassu D. Adaptive multilayer perceptrons with long- and short-term memories // IEEE Transactions On Neural Networks. 2002. V. 13, N 1. P.22-33.
Madureira G., Ruano A.E. A neural network seismic detector // Acta Technica Jaurinensis. 2009. V. 2, N 2. P.159-170.
McEvilly T.V., Majer E.L. ASP: An automated seismic processor for microearthquake networks // Bull. Seismol. Soc. Amer. 1982. V. 72, N 1. P.303-325.
Plešinger A., Rŭžek B., Boušková A. Statistical interpretation of WEBNET seismograms by artificial neural nets // Studia Geophysica et Geodaetica. 2000. V. 44, N 2. P.251-271.
Reading A., Mao W., Gubbins D. Polarization filtering for automatic picking of seismic data and improved converted phase detection // Geophys. J. Int. 2001. V. 147, N 1. P.227-234.
Scarpetta S., Giudicepietro F., Ezin E.C., Petrosino S., Del Pezzo E., Martini M., Marinaro M. Automatic classification of seismic signals at Mt. Vesuvius Volcano, Italy, using neural networks // Bull. Seismol. Soc. Amer. 2005. V. 95, N 1. P.185-196.
Sick B., Guggenmos M., Joswig M. Chances and limits of single-station seismic event clustering by unsupervised pattern recognition // Geophys. J. Int. 2015. V. 201, N 3. P.1801-1813.
Williams R.J., Zipser D. A learning algorithm for continually running fully recurrent neural networks // Neural Computation. 1989. V. 1. P.270-280.
Wiszniowski J., Plesiewicz B.M., Trojanowski J. Application of real time recurrent neural network for detection of small natural earthquakes in Poland // Acta Geophysica. 2014. V. 62, N 3. P.469-485.
Withers M., Aster R., Young C., Beiriger J., Harris M., Moore S., Trujillo J. A comparison of select trigger algorithms for automated global seismic phase and event detection // Bull. Seismol. Soc. Amer. 1998. V. 88, N 1. P.95-106.
Zhang H., Thurber C., Rowe C. Automatic P-wave arrival detection and picking with multiscale wavelet analysis for single-component recording // Bull. Seismol. Soc. Amer. 2003. V. 93, N 5. P.1904-1912.
