基于TEI@I方法论的航空客运需求预测模型  

Air Passenger Demand Forecasting Model Based on TEI@I Methodology

作　　者：梁小珍[1] 张倩文 杨明歌[1] Liang Xiaozhen;Zhang Qianwen;Yang Mingge(School of Management,Shanghai University,Shanghai 200444)

机构地区：[1]上海大学管理学院,上海200444

出　　处：《管理评论》2020年第7期180-190,共11页Management Review

基　　金：国家自然科学基金项目(71701122,71702095,11801352)。

摘　　要：本文以TEI@I方法论为指导,提出了一个航空客运需求预测的研究框架。首先对航空客运需求时间序列进行EEMD分解,从数据驱动的角度出发,对各子序列的复杂性、平稳性、长程相关性等特征进行分析,并根据其不同特征选择合适的计量经济学模型或者人工智能模型进行预测,然后采用专家系统处理航空客运市场中的突现性和不稳定性,最后将上述几部分进行集成从而获得一个更为精确的预测结果。实证研究表明,基于TEI@I方法论的航空客运需求预测模型的预测效果远远优于其他基准模型。Based on TEI@I methodology,this paper proposes a forecasting framework on air passenger demand.First,ensemble empiri-cal mode decomposition(EEMD)is applied to decompose the original air passenger demand data into a number of relatively simple modes,reducing the complexity of the data.Second,the extracted modes are thoroughly analyzed to capture hidden data characteristics,including complexity,stationarity and long-range correlation properties.These characteristics are then used to determine appropriate fore-casting models for each mode(econometric models or artificial intelligence models).After that,the impacts of irregular and the infre-quent future factors on air passenger demand are explored using expert systems techniques.Finally,the components above are predicted independently and these prediction results are combined as an aggregated output.The empirical results indicate that the proposed model based on TEI@I methodology has a good prediction performance on air passenger demand.

关 键 词：TEI@I方法论 航空客运需求 去趋势波动分析法 样本熵 长短期记忆模型 

分 类 号：F224[经济管理—国民经济] F562