• DocumentCode
    2306859
  • Title

    Determination of the Fault Zone By Using Genetic Celluar Neular Network in the Thrace and the Marmara Sea

  • Author

    Caglak, F. ; Albora, A. Muhittin ; Ucan, O.N.

  • Author_Institution
    Fen Bilimleri Estitusu, Istanbul Univ.
  • fYear
    2006
  • fDate
    17-19 April 2006
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this paper, we attempted to determine the location of fault zone using the genetic cellular neural network method (G-CNN) in the Thrace and the Marmara Sea regions. G-CNN is a method used to detect specific feature of the 2-D image in the image-processing technique. Genetic algorithm has been used for as learning algorithm in the G-CNN. The G-CNN method has been used for determining the fault zone, as detect regional and residual effect of the gravity anomaly map. Regional anomaly map has been modelled accordingly and compared to the available seismic data. The fault zones in these regions have been determined by way of companion of the fault model with geological data the outcome of which ultimately gives complete accord
  • Keywords
    cellular automata; cellular neural nets; feature extraction; genetic algorithms; geophysical techniques; image processing; seismic waves; 2-D image; G-CNN; Marmara Sea; Thrace; fault zone determination; feature detection; genetic algorithm; genetic cellular neural network; geological data; gravity anomaly map; image-processing technique; seismic data; Cellular neural networks; Computer vision; Fault detection; Genetic algorithms; Geology; Gravity; Intelligent networks; Piecewise linear techniques;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications, 2006 IEEE 14th
  • Conference_Location
    Antalya
  • Print_ISBN
    1-4244-0238-7
  • Type

    conf

  • DOI
    10.1109/SIU.2006.1659871
  • Filename
    1659871