Analysis of Factors in Flight Delay
Authors
Yiyang Xu, Luyao Liu, Xichen Gao, Fanyu Frank Zeng
Corresponding Author
Fanyu Frank Zeng
Available Online December 2019.
- DOI
- 10.2991/mmsta-19.2019.36How to use a DOI?
- Keywords
- flight delay; multiple linear regression; modeling, prediction; machine learning
- Abstract
With the advancement of air transport industry, airline travelling is becoming increasingly prevalent in recent years. Flight delay, however, has been a headache and costly issue for both air companies and travelers, leading to inconvenience in our daily life. We can't help asking: what's the major cause for flight delay? In this paper, visualization and multiple linear regression are implemented based on Chinese flight data. Temperature, previous delay rate, month and weekday are figured out as influential factors. Further improvements are made by extracting variables to explore the optimal regression mathematical model. Then, machine learning algorithms are introduced to make future predictions.
- Copyright
- © 2019, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yiyang Xu AU - Luyao Liu AU - Xichen Gao AU - Fanyu Frank Zeng PY - 2019/12 DA - 2019/12 TI - Analysis of Factors in Flight Delay BT - Proceedings of the 2019 2nd International Conference on Mathematics, Modeling and Simulation Technologies and Applications (MMSTA 2019) PB - Atlantis Press SP - 170 EP - 176 SN - 2352-538X UR - https://doi.org/10.2991/mmsta-19.2019.36 DO - 10.2991/mmsta-19.2019.36 ID - Xu2019/12 ER -