Abstract
Abstract—A lot of factors that affect the overall price of airline tickets, including the airline, the date of travel, source, destination, route, duration, and so on. Each provider seems to have its own unique set regulations and methods for determining pricing. Recent breakthroughs in Artificial Intelligence (AI) and Machine Learning (ML) allow for the inference of such principles as well as the modelling of price volatility. This article is a study conducted on predicting flight prices. Utilizing two datasets for testing and training, this study analyses various machine learning methods for predicting flight prices. Keywords—artificial Intelligence, machine learning, air price, prediction model, dataset
Publisher
International Journal for Research in Applied Science and Engineering Technology (IJRASET)
Subject
General Earth and Planetary Sciences,General Environmental Science
Cited by
3 articles.
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