This paper discusses the issue of airfare. A set of characteristics defining a typical flight is chosen for this purpose, with the assumption that these characteristics influence the price of an airline ticket. Flight ticket prices fluctuate depending on different parameters such as flight schedule, destination, and duration, a variety of occasions such as vacations or the holiday season. As a result, having a basic understanding of flight rates before booking a vacation will undoubtedly save many individuals money and time. Analysing 3 datasets to get insights about the airline fare and the features of the three datasets are applied to the seven different machine learning (ML) models which are used to predict airline ticket prices, and their performance is compared. The goal is to investigate the factors that determine the cost of a flight. The data can then be used to create a system that predicts flight prices.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Airline Fare Prediction Using Machine Learning Algorithms


    Beteiligte:


    Erscheinungsdatum :

    20.01.2022


    Format / Umfang :

    916142 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Prediction of Flight-fare using machine learning

    Alapati, Naresh / Prasad, B.V.V.S. / Sharma, Aditi et al. | IEEE | 2022


    Airline pricing and fare product differentiation

    Botimer, Theodore Charles | DSpace@MIT | 1994

    Freier Zugriff

    Airline pricing and fare product differentiation

    Botimer, Theodore Charles | DSpace@MIT | 1993

    Freier Zugriff


    Causes and Consequences of Airline Fare Wars

    Morrison, S. A. / Winston, C. / Transportation Research Forum | British Library Conference Proceedings | 1996