A combination selection algorithm on forecasting

Shuang Cang, Hongnian Yu

Research output: Contribution to journalArticlepeer-review

34 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 Sep 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