Sunspot numbers forecasting using neural networks

A recurrent connectionist network has been designed to model sunspot data. The network architecture, sunspot data, and statistical models are described, and experimental results are provided. This preliminary experimental work shows that the network can produce competitive prediction results that compare with those of traditional autoregressive models. The method is not problem specific and could be applied to other problems in dynamical system modeling, recognition, prediction, and control fields.<<ETX>>