Prediction of Flight Areas using Machine Learning Algorithm

Anyone who often uses the airways wants to predict when it will be best to purchase a ticket in order to get the best possible value. Aircraft firms continuously adjust ticket prices in an effort to maximize profits. When it's anticipated that demand for more income will grow, aircraft manufacturers may raise flying prices. Information analysis for a given air route, comprising the features like take-off time, entrance time, and airways during a specified period, has been gathered in order to decrease costs. To use the machine learning models, qualities are arranged based on the information that has been gathered. The machine learning approach to determine costs based on attributes is presented in the paper below.

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Publication Details

Journal
LatIA
Published
2024-08-21
DOI
https://doi.org/10.62486/latia202493
Citations
4
Primary Topic
Air Traffic Management and Optimization
Type
article
Field-Weighted Citation Impact
5.20
Controls
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article

Prediction of Flight Areas using Machine Learning Algorithm

Khushwant Singh, Vugar Hacimahmud Abdullayev, Mohit Yadav
4 citations
LatIA
Air Traffic Management and Optimization
5.20
article

Prediction of Flight Areas using Machine Learning Algorithm

Khushwant Singh, Vugar Hacimahmud Abdullayev, Mohit Yadav
article en
4 citations

Abstract

Anyone who often uses the airways wants to predict when it will be best to purchase a ticket in order to get the best possible value. Aircraft firms continuously adjust ticket prices in an effort to maximize profits. When it's anticipated that demand for more income will grow, aircraft manufacturers may raise flying prices. Information analysis for a given air route, comprising the features like take-off time, entrance time, and airways during a specified period, has been gathered in order to decrease costs. To use the machine learning models, qualities are arranged based on the information that has been gathered. The machine learning approach to determine costs based on attributes is presented in the paper below.

LatIAVol. 2
Chandigarh University (IN), Azerbaijan State Oil and Industry University (AZ), Maharshi Dayanand University (IN)
No poverty
Openalex Percentile: Top 5%
Air Traffic Management and Optimization
5.20
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