• DocumentCode
    3299448
  • Title

    Magnitude of Earthquake Prediction Using Neural Network

  • Author

    Suratgar, Amir Abolfazl ; Setoudeh, Farbod ; Salemi, Amir Hossein ; Negarestani, Ali

  • Author_Institution
    Electr. Eng. Dept., Arak Univ., Arak
  • Volume
    2
  • fYear
    2008
  • fDate
    18-20 Oct. 2008
  • Firstpage
    448
  • Lastpage
    452
  • Abstract
    This paper presents a new method for earthquake prediction. In the proposed method the variation of geomagnetic field declination, horizontal component and hourly relative humidity, temperature ground, rainy rate per day such as hum, rrr (the average of rainy hours time per day), and tgtg (temperature ground) are used to predict magnitude of earthquake 2 days before the occurrence of earthquake occurrence by using a neural network. As a case study, earth geomagnetic field measured data is used. The data are driven from the measurements collected in Tehran Geophysics Research Center in 1970 - 1976. Simulation results are very promising.
  • Keywords
    atmospheric humidity; earthquakes; geomagnetism; geophysical techniques; geophysics computing; neural nets; rain; AD 1970 to 1976; Tehran Geophysics Research Center; earth geomagnetic field measured data; earthquake magnitude prediction; earthquake occurrence; geomagnetic field declination; neural network; rainy rate; relative humidity; temperature ground; Earth; Earthquakes; Electromagnetic radiation; Geomagnetism; Geophysical measurement techniques; Geophysical measurements; Ground penetrating radar; Land surface temperature; Neural networks; Seismic measurements; Earth; Magnetic; Neural network; Quake;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2008. ICNC '08. Fourth International Conference on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-0-7695-3304-9
  • Type

    conf

  • DOI
    10.1109/ICNC.2008.781
  • Filename
    4667035