摘要
构建SD-ARIMAp,d,qsp,sd,sqS1复合模型,使用剔除季节趋势后的月度客流量数据对上海虹桥机场2008年1月至2017年12月数据进行建模,以2018年1~8月虹桥机场旅客吞吐量数据作为测试集进行预测验证。结果发现:虹桥机场客流量呈现出冬季偏低的季节性波动趋势;SD-ARIMA复合模型对时间序列极端值数据更为耐受,对客运量表现出较好的拟合效果。通过对模型不同角度的性能分析,本研究构建的SD-ARIMA复合模型具备一定的有效性及优越性,可用于短期的机场客流量预测,同时对机场的运营及资源调配等方面具有一定参考价值。
Construct a SD-ARIMAp,d,qsp,sd,sqS1 composite model,modeling data from January 2008 to December 2017 at Shanghai Hongqiao Airport using monthly passenger flow data after eliminating seasonal trends,the passenger throughput data of Hongqiao Airport from January to August 2018 was used as a test set for predictive verification.The results show that the passenger flow of Hongqiao Airport shows a seasonal fluctuation trend of low winter;the SD-ARIMA composite model is more tolerant to time series extreme value data and shows a good fitting effect on passenger traffic.Through the performance analysis of different angles of the model,the SD-ARIMA composite model constructed in this study has certain effectiveness and superiority,which can be used for short-term airport passenger flow forecasting,and has certain reference value for airport operation and resource allocation.
作者
杨梦达
戴晨斌
冀和
樊重俊
YANG Mengda;DAI Chenbin;JI He;FAN Chongjun(Management School,University of Shanghai for Science and Technology,Shanghai 200093,China;Shanghai Airport(Group)Technology Center,Shanghai 200335,China)
出处
《物流科技》
2019年第11期74-77,87,共5页
Logistics Sci-Tech
基金
国家自然科学基金资助项目(71774111)
