Flight Fare Prediction Using Machine Learning Approach

Autor: Fardeen Shaikh, Sanchita Yelgate, Nilam Jadhav, Preshita Ingale, Swapnil Korade
Rok vydání: 2023
Předmět:
Zdroj: International Journal for Research in Applied Science and Engineering Technology. 11:1332-1334
ISSN: 2321-9653
DOI: 10.22214/ijraset.2023.49224
Popis: In the airline industry, ticket pricing is a complex process that is influenced by various factors, including demand, availability, and competition. Pricing strategies that enable airlines to maximize profits while maintaining customer satisfaction are therefore essential. By analysing historical data, machine learning algorithms can identify a minimum airfare, data for a specific air route has been collected including the features like arrival time, departure time and airways over a specific time period, features are extracted from the collected data to apply Machine Learning (ML) models.
Databáze: OpenAIRE