A combination selection algorithm on forecasting

Shuang Cang, Hongnian Yu

    Research output: Contribution to journalArticlepeer-review

    42 Citations (Scopus)

    Abstract

    It is widely accepted in forecasting that a combination model can improve forecasting accuracy. One important challenge is how to select the optimal subset of individual models from all available models without having to try all possible combinations of these models. This paper proposes an optimal subset selection algorithm from all individual models using information theory. The experimental results in tourism demand forecasting demonstrate that the combination of the individual models from the selected optimal subset significantly outperforms the combination of all available individual models. The proposed optimal subset selection algorithm provides a theoretical approach rather than experimental assessments which dominate literature.
    Original languageEnglish
    Pages (from-to)127-139
    Number of pages13
    JournalEuropean Journal of Operational Research
    Volume234
    Issue number1
    Early online date8 Sept 2013
    DOIs
    Publication statusPublished - 1 Apr 2014

    Fingerprint

    Dive into the research topics of 'A combination selection algorithm on forecasting'. Together they form a unique fingerprint.

    Cite this