An Extrapolation Approach for RF-EMF Exposure Prediction in an Urban Area using Artificial Neural Network
نویسندگان
چکیده
The prediction of the electric (E) field plays an important role in monitoring radiofrequency electromagnetic (RF-EMF) exposure induced by cellular networks. In this paper, we present approach to extrapolate E urban area using artificial neural network. We first apply a moving average method over sliding window out EMF random fluctuations and remove noise produced during drive test recording measurements along route. Using public accessed datasets, i.e., cartoradio OpenStreetMap, then extract relevant features, including ones that have relation with number active antennas those used Bertoni-Walfisch propagation model. By applying Gram-Schmidt Orthogonalization procedure, select best subset extracted features as inputs network (ANN). work, two disjoint subsets are selected for learning testing phases evaluate performance our proposal extrapolation quantify uncertainty generated proposed predictor due dynamicity usage networks geolocalization inaccuracies.
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2023
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2023.3280125