基于TEI@I方法论的航空客运需求预测模型

管理评论 ›› 2020, Vol. 32 ›› Issue (7): 180-190.

基于TEI@I方法论的航空客运需求预测模型

梁小珍, 张倩文, 杨明歌

上海大学管理学院, 上海 200444

收稿日期:2019-05-17 出版日期:2020-07-28 发布日期:2020-08-08
通讯作者: 杨明歌(通讯作者),上海大学管理学院副教授,硕士生导师,博士
作者简介:梁小珍,上海大学管理学院讲师,硕士生导师,博士;张倩文,上海大学管理学院硕士研究生。
基金资助:
国家自然科学基金项目（71701122；71702095；11801352）。

Air Passenger Demand Forecasting Model Based on TEI@I Methodology

Liang Xiaozhen, Zhang Qianwen, Yang Mingge

School of Management, Shanghai University, Shanghai 200444

Received:2019-05-17 Online:2020-07-28 Published:2020-08-08

摘要/Abstract

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。

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

Abstract: Based on TEI@I methodology, this paper proposes a forecasting framework on air passenger demand. First, ensemble empirical 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 forecasting models for each mode (econometric models or artificial intelligence models). After that, the impacts of irregular and the infrequent 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.

Key words: TEI@I methodology, air passenger demand, detrended fluctuation analysis, sample entropy, long and short-term memory model

梁小珍, 张倩文, 杨明歌. 基于TEI@I方法论的航空客运需求预测模型[J]. 管理评论, 2020, 32(7): 180-190.

Liang Xiaozhen, Zhang Qianwen, Yang Mingge. Air Passenger Demand Forecasting Model Based on TEI@I Methodology[J]. Management Review, 2020, 32(7): 180-190.

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