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ademandforecastingmethodbasedonstochasticfrontieranalysisandmodelaverageanapplicationinairtraveldemandforecasting
Zhang Xinyu1; Zheng Yafei2; Wang Shouyang1
2019
Source Publicationjournalofsystemsscienceandcomplexity
ISSN1009-6124
Volume32Issue:2Pages:615
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.
Language英语
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/40796
Collection系统科学研究所
Affiliation1.中国科学院数学与系统科学研究院
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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