Combined Neural Networks for Time Series Analysis

We propose a method for improving the performance of any net(cid:173) work designed to predict the next value of a time series. Vve advo(cid:173) cate analyzing the deviations of the network's predictions from the data in the training set. This can be carried out by a secondary net(cid:173) work trained on the time series of these residuals. The combined system of the two networks is viewed as the new predictor. We demonstrate the simplicity and success of this method, by apply(cid:173) ing it to the sunspots data.