System for Automatic Recognition of Types of Sources of Regional Seismic Events

被引:2
作者
Asming, V. E. [1 ]
Asming, S. V. [1 ]
Fedorov, A. V. [1 ]
Yevtyugina, Z. A. [1 ]
Chigerev, Ye. N. [2 ]
Kremenetskaya, E. O. [1 ]
机构
[1] Russian Acad Sci, Geophys Survey, Kola Branch, Apatity 184200, Murmansk oblast, Russia
[2] Russian Acad Sci, Fed Res Ctr Comp Sci & Control, Dorodnicyn Comp Ctr, Moscow 119333, Russia
关键词
seismic event; earthquake; explosion; discrimination; Bayesian belief network;
D O I
10.3103/S0747923922050036
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
An approach to recognizing the types of seismic event sources is proposed, based on the combination of several heterogeneous parameters of event records and information about the territory where the seismic event occurred. The following recording parameters are used: the ratio of the amplitudes of body waves, the ratio of parts of the spectra at high and low frequencies, the magnitude, and the spectral constancy parameter. Territorial information includes data on the presence of waterbodies, glaciers, mines, and simplified information on natural seismic activity. Their joint use is done with a special type of Bayesian belief network. The decisions made by the network are probabilistic in nature; the probability is understood in the Bayesian sense, i.e., as the degree of confidence in the truth of the judgment, which consists in attributing an event to one of the types (mine explosion, other explosion on land, underwater explosion, earthquake, icequake). The approach is implemented as a software system, which is included in the program for the interactive analysis of seismic event records LOS.
引用
收藏
页码:509 / 520
页数:12
相关论文
共 21 条
  • [1] Seismic event identification
    Anderson, Dale N.
    Randall, George E.
    Whitaker, Rodney W.
    Arrowsmith, Stephen J.
    Arrowsmith, Marie D.
    Fagan, Deborah K.
    Taylor, Steven R.
    Selby, Neil D.
    Schult, Frederick R.
    Kraft, Gordon D.
    Walter, William R.
    [J]. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS, 2010, 2 (04): : 414 - 432
  • [2] Asming V.E., 2017, P 12 INT SEISM SCH M, P33
  • [3] Batyrshin I.Z., 2007, NECHETKIE GIBRIDNYE
  • [4] Constructing a Hidden Markov Model based earthquake detector: application to induced seismicity
    Beyreuther, Moritz
    Hammer, Conny
    Wassermann, Joachim
    Ohrnberger, Matthias
    Megies, Tobias
    [J]. GEOPHYSICAL JOURNAL INTERNATIONAL, 2012, 189 (01) : 602 - 610
  • [5] EXPLAINING THE GIBBS SAMPLER
    CASELLA, G
    GEORGE, EI
    [J]. AMERICAN STATISTICIAN, 1992, 46 (03) : 167 - 174
  • [6] Cox R. T., 2001, Algebra of probable inference
  • [7] Discrimination of Mine Seismic Events and Blasts Using the Fisher Classifier, Naive Bayesian Classifier and Logistic Regression
    Dong, Longjun
    Wesseloo, Johan
    Potvin, Yves
    Li, Xibing
    [J]. ROCK MECHANICS AND ROCK ENGINEERING, 2016, 49 (01) : 183 - 211
  • [8] Fedorov A.V., 2019, SOVR MET OBR INT SEI
  • [9] Spectral analysis of underwater explosions in the Dead Sea
    Gitterman, Y
    Ben-Avraham, Z
    Ginzburg, A
    [J]. GEOPHYSICAL JOURNAL INTERNATIONAL, 1998, 134 (02) : 460 - 472
  • [10] Godzikovskaya A.A, 1995, MESTNYE VZRYVY ZEMLE