Nonlinear Dilation Network for Prediction Applications

Abstract

This paper presents a neural network that introduce a nonlinear dilation function emulating the nonlinearity of the human sensors, say ear. The introduction of the dilation function reduces redundancy in the information contents of the input variables. This results in minimizing the prediction error as well as the error variance. The applications of time-series prediction and the instantaneous VAr prediction of electric arc furnace are included to corroborate the performance of the nonlinear dilation network.