The prediction of the electric field level in the reverberation chamber depending on position of stirrer
This study presents nine modeling techniques within data mining process for the prediction of electric field level which depends on the positions of stirrer in the mode stirred reverberation chamber. These are Linear Regression (LR), Multi Layer Perceptron (MLP), Pace Regression (PR), KStar, Regression by discretization (RD), Random SubSpace (RS), M5P, RepTree and Decision Table models. Relations depending on frequency and position of stirrer have been carried out for the determination of electric field in the reverberation chamber. Obtained model results for each stirrer steps have been compared and the best model has been investigated. Results indicate that the use of derived formulation from these techniques will facilitate design and optimize of location of maxima (mode) and minima (null) of electric field in the reverberation chamber which a component of especially mode stirrer reverberation chamber test method.
electric field reverberation chamber data mining