Theoretical and Natural Science
- The Open Access Proceedings Series for Conferences
Theoretical and Natural Science
Vol. 31, 02 April 2024
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International flight fare prediction and analysis of factors impacting flight fare
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Abstract
In the rapidly evolving landscape of global travel, understanding international flight prices has become pivotal for both travellers and airlines. This paper delves into the intricate web of factors influencing flight prices, utilizing a dataset from “Ease My Trip” spanning 50 days. Employing rigorous data processing techniques, including handling missing values and label encoding, the study explores correlations between various parameters such as cabin class, flight numbers, airlines, and duration, shedding light on pricing dynamics. The research employs linear regression, decision trees, and random forest models for prediction. The results showcase the significance of class, flight numbers, and duration on prices. Particularly, higher cabin classes correlate strongly with increased prices, offering vital insights for airlines to optimize revenue. The models’ predictive accuracies are commendable, with the random forest model standing out, explaining 98.9% of the variance. This study not only illuminates the complex interplay of factors steering international flight prices but also provides airlines with robust pricing strategies. The findings empower travellers to make informed decisions, promising a harmonious future for the aviation industry in an ever-changing global market.
Keywords
International flight prices, pricing strategies, predictive modeling, random forest regression
References
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 3rd International Conference on Computing Innovation and Applied Physics
- ISBN (Print)
- 978-1-83558-317-3
- ISBN (Online)
- 978-1-83558-318-0
- Published Date
- 02 April 2024
- Series
- Theoretical and Natural Science
- ISSN (Print)
- 2753-8818
- ISSN (Online)
- 2753-8826
- DOI
- 10.54254/2753-8818/31/20241079
- Copyright
- 02 April 2024
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited