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Zhang Xinyu1; Zheng Yafei2; Wang Shouyang1
Source Publicationjournalofsystemsscienceandcomplexity
AbstractDemand forecasting is often difficult due to the unobservability of the applicable historical demand series. In this study, the authors propose a demand forecasting method based on stochastic frontier analysis (SFA) models and a model average technique. First, considering model uncertainty, a set of alternative SFA models with various combinations of explanatory variables and distribution assumptions are constructed to estimate demands. Second, an average estimate from the estimated demand values is obtained using a model average technique. Finally, future demand forecasts are achieved, with the average estimates used as historical observations. An empirical application of air travel demand forecasting is implemented. The results of a forecasting performance comparison show that in addition to its ability to estimate demand, the proposed method outperforms other common methods in terms of forecasting passenger traffic.
Document Type期刊论文
2.Postdoctoral Working Station, Shenwan Hongyuan Securities Co., Ltd.
Recommended Citation
GB/T 7714
Zhang Xinyu,Zheng Yafei,Wang Shouyang. ademandforecastingmethodbasedonstochasticfrontieranalysisandmodelaverageanapplicationinairtraveldemandforecasting[J]. journalofsystemsscienceandcomplexity,2019,32(2):615.
APA Zhang Xinyu,Zheng Yafei,&Wang Shouyang.(2019).ademandforecastingmethodbasedonstochasticfrontieranalysisandmodelaverageanapplicationinairtraveldemandforecasting.journalofsystemsscienceandcomplexity,32(2),615.
MLA Zhang Xinyu,et al."ademandforecastingmethodbasedonstochasticfrontieranalysisandmodelaverageanapplicationinairtraveldemandforecasting".journalofsystemsscienceandcomplexity 32.2(2019):615.
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