Financial forecasting through unsupervised clustering and neural networks

In this paper, we review our work on a time series forecasting methodology based on the combination of unsupervised clustering and artificial neural networks. To address noise and non-stationarity, a common approach is to combine a method for the partitioning of the input space into a number of subs...

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Veröffentlicht in:	Operational research 2006-05, Vol.6 (2), p.103-127
Hauptverfasser:	Pavlidis, N. G., Plagianakos, V. P., Tasoulis, D. K., Vrahatis, M. N.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial neural networks Clustering Forecasting Foreign exchange rates Landsat satellites Mathematical models Methodology Neural networks Studies Subspaces Time series
Online-Zugang:	Volltext
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