Air transportation demand forecast through Bagging Holt Winters methods
Tiago Mendes Dantas,
Fernando Luiz Cyrino Oliveira and
Hugo Miguel Varela Repolho
Journal of Air Transport Management, 2017, vol. 59, issue C, 116-123
Abstract:
This paper expands the fields of application of combined Bootstrap aggregating (Bagging) and Holt Winters methods to the air transportation industry, a novelty in literature, in order to obtain more accurate demand forecasts. The methodology involves decomposing the time series into three adding components: trend, seasonal and remainder. New series are generated by resampling the Remainder component and adding back the trend and seasonal ones. The Holt Winters method is used to modelling each time series and the final forecast is obtained by aggregating the forecasts set. The approach is tested using data series from 14 countries and the results are compared with five methodology benchmarks (SARIMA, Holt Winters, ETS, Bagged.BLD.MBB.ETS and Seasonal Naive) using Symmetric Mean Absolute Percentage Error (sMAPE). The empirical results obtained with Bagging Holt Winters methods consistently outperform the benchmarks by providing forecasts that are more accurate.
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (24)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0969699716302265
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:jaitra:v:59:y:2017:i:c:p:116-123
DOI: 10.1016/j.jairtraman.2016.12.006
Access Statistics for this article
Journal of Air Transport Management is currently edited by Anne Graham
More articles in Journal of Air Transport Management from Elsevier
Bibliographic data for series maintained by Catherine Liu ().