• DocumentCode
    1959432
  • Title

    A Neural Network tool for the prediction of electromagnetic field in urban environment

  • Author

    Capizzi, G. ; Coco, S. ; Laudan, A.

  • Author_Institution
    DIEES, Catania Univ.
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    60
  • Lastpage
    60
  • Abstract
    In this paper an artificial neural network model is presented for the prediction of electromagnetic field distribution within a region, starting from the knowledge of some field measurements at points, lying on grids uniformly covering the interesting region. The results of the numerical experiments show that this neural predictor can be successfully used for the solution of this kind of inverse problems, by means of very few field measurements at certain points
  • Keywords
    electrical engineering computing; electromagnetic fields; inverse problems; neural nets; artificial neural network tool; electromagnetic field distribution; field measurements; inverse problems; neural predictor; urban environment; Artificial neural networks; Electromagnetic fields; Electromagnetic measurements; Electromagnetic modeling; Intelligent networks; Inverse problems; Neural networks; Neurons; Phase measurement; Predictive models;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electromagnetic Field Computation, 2006 12th Biennial IEEE Conference on
  • Conference_Location
    Miami, FL
  • Print_ISBN
    1-4244-0320-0
  • Type

    conf

  • DOI
    10.1109/CEFC-06.2006.1632852
  • Filename
    1632852