• DocumentCode
    152170
  • Title

    The investigation of iron ore reserve area of bıngöl region by using cellular neural networks (CNN) method

  • Author

    Albora, Ali Muhittin

  • Author_Institution
    Muhendislik Fak. Jeofiz. Muh. Bolumu-Avcilar, Istanbul Univ., İstanbul, Turkey
  • fYear
    2014
  • fDate
    23-25 April 2014
  • Firstpage
    152
  • Lastpage
    155
  • Abstract
    As it is known that separation of regional and regional fields on gravity and magnetic prospecting method is an important issue. The goal is determination of properties and real depth of structures with minimum error. In this study signal-noise ratio is increased in selection depth and it is possible of monitoring of residual structures by using HYSA method. Here, HYSA method was applied on magnetic data collecting from iron deposits in Bingol Region. We separate between residual and regional fields and residual map was obtained.
  • Keywords
    cellular neural nets; geophysical prospecting; minerals; Bıngol region; CNN method; HYSA method; Turkey; cellular neural networks; gravity method; iron ore reserve area; magnetic prospecting method; residual structures; selection depth; Cellular neural networks; Circuit theory; Conferences; Iron; Magnetic separation; Signal processing; Signal processing algorithms; Bingöl region; Cellular Neural Networks; Iron ore; reserve operation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications Conference (SIU), 2014 22nd
  • Conference_Location
    Trabzon
  • Type

    conf

  • DOI
    10.1109/SIU.2014.6830188
  • Filename
    6830188