Evaluating Prediction Models for Airport Passenger Throughput Using a Hybrid Method

Author:

Chen Bin12ORCID,Zhao Xing1,Wu Jin1

Affiliation:

1. Civil Aviation College, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

2. China Civil Aviation Engineering Consulting Co., Ltd., Beijing 100621, China

Abstract

This paper proposes a hybrid evaluation method to assess the prediction models for airport passenger throughput (APT). By analyzing two hundred three airports in China, five types of models are evaluated to study the applicability to different airports with various airport passenger throughput and developing conditions. The models were fitted using the historical data before 2014 and were verified by using the data from 2015–2019. The evaluating results show that the models employed for evaluating perform well in general except that there are insufficient historical data for modelling, or the APT of the airports changes abruptly owing to expansion, relocation or other kinds of external forces such as earthquakes. The more the APT of an airport is, the more suitable the models are for the airport. Particularly, there is no direct relation between the complexity and the predicting accuracy of the models. If the parameters of the models are properly set, time series models, causal models, market share methods and analogy-based methods can be utilized to predict the APT of 88% of studied airports effectively.

Funder

Civil Aviation Administration of China

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference35 articles.

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