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Machine Learning Model for Electric and Magnetic Fields Estimation in the Proximity of Overhead Transmission Lines

This paper considers the application of machine learning models to electric field intensity and magnetic flux density estimation in the proximity of the overhead transmission lines. The machine learning models are applied on two horizontal overhead transmission line configurations at different rated voltages, at height 1 m above ground surface. The obtained results are compared with the results obtained by charge simulation method and Biot-Savart law based method as well as with the field measurement results.

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