Neural networks as a numerical tool to solve the electromagnetic field in an enclosed space
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Abstract
I am responsible for the formulation of preprocessing functions to enhance the efficiency of the simulations made by an Artificial Neural Network of the Electromagnetic Field emitted by a Dipole Antenna in a closed room, ideally a clean room and then evolve towards the grounds of an enclosed factory. The goal is to optimize the position of the antenna to obtain the strongest Received Signal Strength (RSS) with maximum efficiency both in computational and human costs.
I am responsible for the formulation of preprocessing functions to enhance the efficiency of the simulations made by an Artificial Neural Network of the Electromagnetic Field emitted by a Dipole Antenna in a closed room, ideally a clean room and then evolve towards the grounds of an enclosed factory. The goal is to optimize the position of the antenna to obtain the strongest Received Signal Strength (RSS) with maximum efficiency both in computational and human costs.
I am responsible for the formulation of preprocessing functions to enhance the efficiency of the simulations made by an Artificial Neural Network of the Electromagnetic Field emitted by a Dipole Antenna in a closed room, ideally a clean room and then evolve towards the grounds of an enclosed factory. The goal is to optimize the position of the antenna to obtain the strongest Received Signal Strength (RSS) with maximum efficiency both in computational and human costs.