A decomposition-ensemble approach for tourism forecasting

Gang Xie, Yatong Qian and Shouyang Wang

Annals of Tourism Research, 2020, vol. 81, issue C

Abstract: With the frequent occurrence of irregular events in recent years, the tourism industry in some areas, such as Hong Kong, has suffered great volatility. To enhance the predictive accuracy of tourism demand forecasting, a decomposition-ensemble approach is developed based on the complete ensemble empirical mode decomposition with adaptive noise, data characteristic analysis, and the Elman's neural network model. Using Hong Kong tourism demand as an empirical case, this study firstly investigates how data characteristic analysis is used in a decomposition-ensemble approach. The empirical results show that the proposed model outperforms other models in both point and interval forecasts for different prediction horizons, indicating the effectiveness of the proposed approach for forecasting tourism demand, especially for time series with complexity.

Keywords: Tourism demand; Complete ensemble empirical mode decomposition with adaptive noise; Data characteristic analysis; Time series forecasting (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (20)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:anture:v:81:y:2020:i:c:s0160738320300359

DOI: 10.1016/j.annals.2020.102891

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