@inproceedings{2d89b5f238374edfbc418367bd035c03,
title = "COMBINED NEURAL NETWORKS FOR TIME SERIES ANALYSIS",
abstract = "We propose a method for improving the performance of any network designed to predict the next value of a time series. We advocate analyzing the deviations of the network's predictions from the data in the training set. This can be carried out by a secondary network 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 applying it to the sunspots data. The small corrections of the secondary network can be regarded as resulting from a Taylor expansion of a complex network which includes the combined system. We find that the complex network is more difficult to train and performs worse than the two-step procedure of the combined system.",
author = "Iris Ginzburg and David Horn",
note = "Publisher Copyright: {\textcopyright} 1993 Neural information processing systems foundation. All rights reserved.; 6th Advances in Neural Information Processing Systems, NIPS 1993 ; Conference date: 29-11-1993 Through 02-12-1993",
year = "1993",
language = "אנגלית",
series = "Advances in Neural Information Processing Systems",
publisher = "Neural information processing systems foundation",
pages = "224--231",
editor = "J. Cowan and G. Tesauro and J. Alspector",
booktitle = "Advances in Neural Information Processing Systems 6, NIPS 1993",
address = "ארצות הברית",
}