Air passenger flow forecasting using nonadditive forecast combination with grey prediction

Yi-Chung Hu

Journal of Air Transport Management, 2023, vol. 112, issue C

Abstract: Air passenger flow forecasting plays a critical role in managing air transportation. It is important to develop accurate methods for forecasting the flow of passengers to formulate relevant operational plans and the schedule of airports. Even though empirical evidence has shown that forecast combination can improve the prediction accuracy of single-model forecasts, no study in the literature on transportation to date has examined the performance of such combinations to predict the demand for air transport. In light of the usefulness of grey prediction, which does not require applying any statistical test to examine the data at hand, and relationships among forecasts to be reckoned with, this study proposes using the nonadditive Choquet fuzzy integral to nonlinearly synthesize forecasts from four commonly used univariate grey prediction models into composite forecasts. The results of experiments confirmed that the risk arising from the incorrect choice of forecasting models can be eliminated by using forecast combinations. The proposed combination method based on grey prediction significantly outperformed the other competitors considered.

Keywords: Passenger demand; Air transport; Forecast combination; Grey system; Fuzzy integral (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jaitra:v:112:y:2023:i:c:s0969699723000820

DOI: 10.1016/j.jairtraman.2023.102439

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