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            | FULL TEXT IN RUSSIAN  
 Mekhatronika, Avtomatizatsiya, Upravlenie, 2015, vol. 16, no. 3, pp.  147—158DOI: 10.17587/mau/16.147-158
 
 Intelligent  Seismic-Acoustic System for Identifying the Location of the Focus of an  Expected Earthquake A. M. Pashayev1, info@naa.baku.az, A. A. Alizada2, president@science.az, T. A. Aliev3, telmancyber@rambler.ru, A. M. Abbasov4, ali@elm.az, G. A. Guluyev3, scb06@mail.ru, F. G. Pashayev3, pasha.farhad@gmail.com, U. E. Sattarova3, ulker.rzaeva@gmail.com1Azerbaijan National Academy  of Aviation, Az1045, Baku, Azerbaijan Republic,
 2Azerbaijan National Academy of Sciences, Az1001, Baku, Azerbaijan  Republic,
 3Institute  of Control Systems of the Azerbaijan National Academy of Sciences,
 Az1141, Baku, Azerbaijan  Republic,
 4Ministry of Communications and High Technologies,  Az1000, Baku, Azerbaijan Republic
 
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            | Date received: 05.11.14 This paper presents a brief  review of the state-of-the-art in the field of earthquake study and  forecasting. We analyze the principles of the methods for determination of the  coordinates of earthquake focuses by means of ground seismic stations. We  demonstrate that those methods cannot be used in the system for monitoring of  the beginning of the earthquake preparation process (in the network of RNM ASP  stations).As we know, the beginning  of the earthquake process is accompanied by spreading of noisy seismic-acoustic  signals. Theoretically, the system for monitoring of the beginning of the  earthquake process is based on the technologies for seismic-acoustic signal  processing — Robust Noise Monitoring (RNM). The noise characteristics determined  by RNM technologies indicate the beginning of the anomalous seismic processes  (ASP) and, consequently, a possibility of ASP monitoring.
 Considering that the  seismic-acoustic signal can be represented as the sum of the useful signal and  noise (g = X + e
                ), we present the technologies for  determining noise characteristics. It is demonstrated in the paper that a  change in the estimate of the cross-correlation function RXe(m
                 =  0) between the useful signal Õ(iDt) and the noise e(iDt),  noise variance De and the value of noise correlation RXee
                (m
                 = 0) determine the beginning of ASP. One RNM  ASP station determines the beginning of ASP within a radius of about 500 km.  Determination of the location of an expected earthquake requires a network of  RNM ASP stations.
 We analyze the results of  the noise technology-based monitoring of the anomalous seismic processes  performed from July 2010 to June 2014 by nine seismic-acoustic stations built  at the head of 10 m, 200 m, 300 m and 1400—5000 m deep wells. Based on the  results of the experimental data obtained in the period covering over three  years, an intelligent system has been built, which allows us to identify the  location of the zone of an earthquake, using the combinations of time of change  in the estimate of the correlation function between the useful signal and the  noise of the seismic-acoustic information received from different stations  10—20 hours before the earthquake. In the long term, the system can be used by  seismologists as a tool for determination of the location of the zone of an  expected earthquake.
 Keywords: seismic monitoring, anomalous seismic  processes, intelligent seismic-acoustic system, robust noise technology,  processing of seismic-acoustic information, expert system, neural network  forecasting of earthquake zones 
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            | For citation:Pashayev A. M., Alizada A. A., Aliev T. A.,  Abbasov A. M., Guluyev G. A., Pashayev F. G., Sattarova U. E. Intelligent Seismic-Acoustic System for  Identifying the Location of the Focus of an Expected Earthquake, Mekhatronika, Avtomatizatsiya, Upravlenie,  2015, vol. 16, no. 3, pp. 147—158.
 DOI: 10.17587/mau/16.147-158
 Corresponding author:Pashayev Farhat G., PhD, Leading Researcher, Institute of Control  Systems of the Azerbaijan National Academy of Sciences, Az1141, Baku,  Azerbaijan Republic, e-mail: pasha.farhad@gmail.com
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