DocumentCode :
2523938
Title :
170 MHz field strength prediction in urban environment using neural nets
Author :
Balandier, Thierry ; Caminada, Alexandre ; Lemoine, Vincent ; Alexandre, Frédéric
Author_Institution :
CNET, Belfort, France
Volume :
1
fYear :
1995
fDate :
27-29 Sep 1995
Firstpage :
120
Abstract :
In this paper, a semi-empirical model of field strength prediction combining theoretical results of propagation loss algorithms and artificial neural networks is considered. This approach expects to overcome some limitations inherent in existing semi-empirical models: linear behaviour of the statistical analysis used in the construction of the models, unfitness for learning new situations. The good results obtained in a dense urban area show that neural networks are a very efficient empirical method to compute new kinds of models which integrate theoretical and experimental data
Keywords :
VHF radio propagation; electromagnetic fields; land mobile radio; neural nets; statistical analysis; telecommunication computing; 170 MHz; 170 MHz field strength prediction; field strength prediction; neural nets; propagation loss algorithms; semi-empirical model; statistical analysis; urban environment; Antenna measurements; Artificial neural networks; Base stations; Computer networks; Neural networks; Performance evaluation; Predictive models; Propagation losses; Testing; Urban areas;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Personal, Indoor and Mobile Radio Communications, 1995. PIMRC'95. Wireless: Merging onto the Information Superhighway., Sixth IEEE International Symposium on
Conference_Location :
Toronto, Ont.
Print_ISBN :
0-7803-3002-1
Type :
conf
DOI :
10.1109/PIMRC.1995.476416
Filename :
476416
Link To Document :
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