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Hierarchical Multilevel Approaches of Forecast Combination

In: Operations Research Proceedings 2004

Author

Listed:
  • Silvia Riedel

    (Lufthansa Systems Berlin GmbH
    Bournemouth University Poole House)

  • Bogdan Gabrys

    (Bournemouth University Poole House)

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.

Suggested Citation

  • Silvia Riedel & Bogdan Gabrys, 2005. "Hierarchical Multilevel Approaches of Forecast Combination," Operations Research Proceedings, in: Hein Fleuren & Dick Hertog & Peter Kort (ed.), Operations Research Proceedings 2004, pages 479-486, Springer.
    • Handle: RePEc:spr:oprchp:978-3-540-27679-1_59
    DOI: 10.1007/3-540-27679-3_59
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    Cited by:

    1. Banerjee, Nilabhra & Morton, Alec & Akartunalı, Kerem, 2020. "Passenger demand forecasting in scheduled transportation," European Journal of Operational Research, Elsevier, vol. 286(3), pages 797-810.

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