This paper is published in Volume-5, Issue-3, 2019
Area
Computer Science
Author
Purbid Bambroo
Co-authors
Sheetal, Nitin Agrawal, Dr. Kavitha Sooda
Org/Univ
BMS College of Engineering, Bengaluru, Karnataka, India
Pub. Date
10 May, 2019
Paper ID
V5I3-1150
Publisher
Keywords
Neural networks, Machine learning, Airlines, Dynamic pricing

Citationsacebook

IEEE
Purbid Bambroo, Sheetal, Nitin Agrawal, Dr. Kavitha Sooda. Analysis of dynamic pricing in airlines and predicting least fare, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Purbid Bambroo, Sheetal, Nitin Agrawal, Dr. Kavitha Sooda (2019). Analysis of dynamic pricing in airlines and predicting least fare. International Journal of Advance Research, Ideas and Innovations in Technology, 5(3) www.IJARIIT.com.

MLA
Purbid Bambroo, Sheetal, Nitin Agrawal, Dr. Kavitha Sooda. "Analysis of dynamic pricing in airlines and predicting least fare." International Journal of Advance Research, Ideas and Innovations in Technology 5.3 (2019). www.IJARIIT.com.

Abstract

Airline companies have been using dynamic pricing to vary the ticket prices to maximize the profit for a limited number of seats. Though the algorithm is different for all the airlines and never disclosed, it is possible to predict the variation in ticket prices. There have been studies in the past for the same, none explicitly for the Indian market; considering the major holidays. Applying techniques from Machine learning model of neural networks and backpropagation, we could predict the upcoming surge or dip in the ticket prices. We aim at predicting if the price of the ticket will go down in the future or the current price is the lowest.
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