Time Series Prediction with Multilayer Perception, FIR and Elman Neural Networks

Multilayer perceptron network (MLP), FIR neural network and Elman neural network were compared in four different time series prediction tasks. Time series include load in an electric network series, fluctuations in a far-infrared laser series, numerically generated series and behaviour of sunspots series. FIR neural network was trained with temporal backpropagation learning algorithm. Results show that the efficiency of the learning algorithm is more important factor than the network model used. Elman network models load in an electric network series better than MLP network and in other prediction tasks it performs similar to MLP network. FIR network performs adequately but not as good as Elman network.