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• W2763881501 abstract "In recent years, increasing energy demand has resulted in more loading in power transmission lines and correspondingly more electric and magnetic field occurrence. In this paper, electric and magnetic field levels around high voltage power transmission lines are measured and then calculated analytically by simulating the realistic case. Moreover, the field levels around these power lines have been predicted using multilayer perceptron artificial neural network (ANN) and generalized regression neural network models. Typical 154 kV power transmission line facilities of Turkey have been studied. Electric and magnetic field levels in the proximity of power transmission lines have been predicted with ANN models with high accuracies. Particularly, the MLPNN algorithm predicts the electric and magnetic field intensities with very high precision. The aim of this research is to create a reference for researchers focused on topics of occupational and general public exposures and also biological effects of electric and magnetic fields emitted from low-frequency power transmission lines." @default.
• W2763881501 created "2017-10-20" @default.
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• W2763881501 date "2017-01-01" @default.
• W2763881501 modified "2023-10-17" @default.
• W2763881501 title "Low-frequency exposure analysis using electric and magnetic field measurements and predictions in the proximity of power transmission lines in urban areas" @default.
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• W2763881501 doi "https://doi.org/10.3906/elk-1608-312" @default.
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