Hierarchical Multilevel Approaches of Forecast Combination.

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Riedel, S. and Gabrys, B., 2004. Hierarchical Multilevel Approaches of Forecast Combination. In: Fleuren, H., den Hertog, D. and Kort, P., eds. Operations Research Proceedings 2004: Selected Papers of the Annual International Conference of the German Operations Research Society (GOR). Jointly Organized with the Netherlands Society for Operations Research (NGB) Tilburg, September 1–3, 2004. Springer Berlin Heidelberg, pp. 479-486.

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Official URL: http://www.springerlink.com/content/h67h8806h3554j...

DOI: 10.1007/3-540-27679-3_59

Abstract

In this paper the approach of combining predictions is used to benefit from the advantages of forecasts predicting on different levels, to reduce the risks of high noise terms on low level predictions and overgeneralization on higher levels. The presented experimentally compared approaches of combining seasonal airline demand forecasts differ concerning input decomposition, multilevel structures, combination models and kinds of aggregation. Significant forecast improvements have been obtained when using multilevel, hierarchical structures.

Item Type:Book Section
ISBN:978-3-540-24274-1
Series Name:Operations Research Proceedings
Series Name:Operations Research Proceedings
Subjects:Generalities > Computer Science and Informatics > Artificial Intelligence
Generalities > Computer Science and Informatics
Group:School of Design, Engineering & Computing > Smart Technology Research Centre
ID Code:8532
Deposited By:INVALID USER
Deposited On:20 Dec 2008 19:02
Last Modified:07 Mar 2013 15:02
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