Prediction of shielding effectiveness of cement-graphite powder using artificial neural network

This paper presents the method to predict the shielding effectiveness of cement powder mixed with different amount of graphite powder. cement mixed with different percentage of graphite is prepared. their dielectric constant and loss tangent are measured based on the transmission/reflection technique using apc7 connector. the measured data is fed into artificial neural network (ann) for training. when the training process is completed the neural network is used to predict the dielectric constant and loss tangent of cement-graphite mixture that contains different amount of graphite. the comparison shows that the trained neural network is very successful to predict the dielectric constant and loss tangent of cement-graphite mixture. the proposed graphical user interface has made the process of shielding effectiveness prediction becomes more user friendly especially for those designers who are not familiar with the analytical calculation of shielding effectiveness and dielectric measurement. © 2016 penerbit utm press. all rights reserved.