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Prediction System for Flight Prices Using Machine Learning

Author(s):

Shreyas Nanaware , Dr.D.Y.Patil college of engineering,ambi,pune; Saurabh Bansude, Dr.D.Y.Patil college of engineering,ambi,pune; Babasaheb Rashinkar, Dr.D.Y.Patil college of engineering,ambi,pune; Preeti Nimbargi, Dr.D.Y.Patil college of engineering,ambi,pune

Keywords:

Machine Learning, Modelling, Comparative Analysis, Artificial Intelligence

Abstract

With varying plane ticket costs, domestic air travel is becoming increasingly popular in India. As more Internet booking channels emerge, passengers attempt to figure out how these airlines make decisions about ticket prices over time. Knowing the best travel time and the best spot to stay is also important. A sufficient amount is required. Unfortunately, dynamic pricing is typically implemented programmatically and is depending on specific hidden criteria (e.g., number of days till aircraft departure or number of tickets remaining). The research focuses on mining historical airfare data and using data modeling techniques to forecast price variations over time so that customers can benefit. This paper document study conducted to understand the traveling costs and will be helpful for the users to manage their entire traveling cost.

Other Details

Paper ID: IJSRDV11I30269
Published in: Volume : 11, Issue : 3
Publication Date: 01/06/2023
Page(s): 349-351

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