Data Analysis and Knowledge Discovery  2020, Vol. 4 Issue (2/3): 192-199    DOI: 10.11925/infotech.2096-3467.2019.0522
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Forecasting Airfare Based on Route Characteristics
Zhong Lizhen1,Ma Minshu1(),Zhou Changfeng2
1School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
2Passenger Transport Department, China State Railway Group Co., Ltd., Beijing 100033, China
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Abstract

[Objective] This paper predicts airfare on routes with fewer daily average flights and incomplete or even no historical data, aiming to help passengers choose better ticketing time.[Methods] We used historical data of multiple routes to predict airfares of the targets. Based on previous research and data, we extracted characteristic variables related to airfare fluctuations. We also classified these variables to establish the airfare forecasting model.[Results] When the model contains variables like the distance and the socio-economic characteristics of the route, the prediction error was significantly reduced.[Limitations] We did not include transit flights and local residents’ income data in our study. More research is needed to evaluate the performance of predicting algorithms.[Conclusions] The characteristics related to the year, the distance between the two places and the socio-economic factors of the routes are the main reasons for airfare fluctuations.

Received: 16 May 2019      Published: 26 April 2020
 ZTFLH: TP393
Corresponding Authors: Ma Minshu     E-mail: mshma@bjtu.edu.cn