ademandforecastingmethodbasedonstochasticfrontieranalysisandmodelaverageanapplicationinairtraveldemandforecasting

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	ademandforecastingmethodbasedonstochasticfrontieranalysisandmodelaverageanapplicationinairtraveldemandforecasting
	Zhang Xinyu1 ; Zheng Yafei 2; Wang Shouyang1
	2019-01-01
发表期刊	journalofsystemsscienceandcomplexity
ISSN	1009-6124
卷号	32 期号:2 页码:615
摘要	Demand 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.
语种	英语
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/40796
专题	系统科学研究所
作者单位	1.中国科学院数学与系统科学研究院 2.Postdoctoral Working Station, Shenwan Hongyuan Securities Co., Ltd.
推荐引用方式 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.