A Neural Network Model to Predict the Radiation Resistance of Dipole Antenna

This paper presented a multi-layer neural network model for the calculation of the radiation resistance of a dipole antenna. The network is trained using the data generated from the TaraNG solver. The data consist of radiation resistances and their corresponding frequencies. The proposed neural network structure is 1-20-20-20-1. The model contains one input layer, three hidden layers and one output layer. The predicted result is well agreed with TaraNG solver results.