Prediction of Flight-fare using machine learning

Abstract

Passengers are attempting to grasp how these airline businesses make judgments regarding flight ticket costs over time, since demand for air travel in India is growing more popular with multiple flight tickets purchasing on the internet. There are a variety of strategies that allow you to perform things at the right moment. Customers want the cheapest ticket possible, but airlines want to maximize their profit by keeping their entire income as high as feasible. To increase revenue, airlines use a number of computational tactics, including as demand forecasting and pricing discrimination. This is for the consumer who buys a flight ticket by estimating the amount of the flight fare. The major difficulty from the customer’s perspective, finding the perfect value or the ideal time to purchase tickets is the most difficult component. The bulk of the techniques rely on advanced computational intelligence, prediction models, and a branch of science called Machine Learning (ML). This research emphasizes the factors and provides instructions for developing a machine learning-based aircraft fare prediction model.