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Hybrid ICA - ANN model applied to volatile time series forecasting

Gorriz , J. M. and Puntonet, Carlos G. and Lang, Elmar (2004) Hybrid ICA - ANN model applied to volatile time series forecasting. Proc. Int. Conf. on Artificial Intelligence and Applications (AIA) 411, p. 815.

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Other URL: http://www.actapress.com/Content_of_Proceeding.aspx?proceedingID=49


Abstract

In this paper we propose a new method for volatile time series forecasting using Independent Component Analysis (ICA) algorithms and Savitzky-Golay filtering as preprocessing tools. The preprocessed data will be introduce in a based radial basis functions (RBF) Artificial Neural Network (ANN) and the prediction result will be compared with the one we get without these preprocessing tools or the classical Principal Component Analysis (PCA) tool.


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Item Type:Article
Date:2004
Institutions:Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang
Projects:Graduiertenkolleg Nichtlinearität und Nichtgleichgewicht
Dewey Decimal Classification:500 Science > 530 Physics
500 Science > 570 Life sciences
Status:Published
Refereed:Yes, this version has been refereed
Created at the University of Regensburg:Yes
Deposited On:20 Mar 2007
Last Modified:15 Oct 2010 07:18
Item ID:1641
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