TY - GEN
T1 - ANN applications in detection of precipitation based on the received signal level of commercial microwave links
AU - Dordevic, Vladica
AU - Pronic-Rancic, Olivera
AU - Marinkovic, Zlatica
AU - Milijic, Marija
AU - Markovic, Vera
AU - Siart, Uwe
AU - Chwala, Christian
AU - Kunstmann, Harald
PY - 2013
Y1 - 2013
N2 - Detection of precipitation based on the received signal level of commercial microwave links has been increasingly used in the mountain areas where meteorological radars have limited ranges, and placing rain gauges is impossible due to terrain morphology. In this paper, focused time-delay neural networks were trained and tested, to detect the appearance of precipitation based on the data of the link received signal level. For training and testing the networks the results of the detection of precipitation using one of the previously proposed methods have been used. After choosing the network with the best characteristics for the final model, the detailed testing was done with the data obtained on the same link, which were not used for model development. The results show that the proposed method based on neural networks can be efficiently used instead of the previously proposed method (significantly shorter time of the data processing was achieved by using a neural networks).
AB - Detection of precipitation based on the received signal level of commercial microwave links has been increasingly used in the mountain areas where meteorological radars have limited ranges, and placing rain gauges is impossible due to terrain morphology. In this paper, focused time-delay neural networks were trained and tested, to detect the appearance of precipitation based on the data of the link received signal level. For training and testing the networks the results of the detection of precipitation using one of the previously proposed methods have been used. After choosing the network with the best characteristics for the final model, the detailed testing was done with the data obtained on the same link, which were not used for model development. The results show that the proposed method based on neural networks can be efficiently used instead of the previously proposed method (significantly shorter time of the data processing was achieved by using a neural networks).
KW - detection of precipitation
KW - focused time-delay neural networks
KW - received signal level
UR - http://www.scopus.com/inward/record.url?scp=84893539863&partnerID=8YFLogxK
U2 - 10.1109/TELSKS.2013.6704402
DO - 10.1109/TELSKS.2013.6704402
M3 - Conference contribution
AN - SCOPUS:84893539863
SN - 9781479909025
T3 - 2013 11th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services, TELSIKS 2013
SP - 374
EP - 377
BT - 2013 11th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services, TELSIKS 2013
T2 - 2013 11th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services, TELSIKS 2013
Y2 - 16 October 2013 through 19 October 2013
ER -