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.
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;
Conference_Titel :
Electromagnetic Field Computation, 2006 12th Biennial IEEE Conference on
Conference_Location :
Miami, FL
Print_ISBN :
1-4244-0320-0
DOI :
10.1109/CEFC-06.2006.1632852
