Abstract Decision-making under uncertainty is one of the major issues faced by recent computer-aided solutions and applications. Bayesian prediction techniques come handy in such areas of research. In this paper, we have tried to predict flight fares using Kalman filter which is a famous Bayesian estimation technique. This approach presents an algorithm based on the linear model of the Kalman Filter. This model predicts the fare of a flight based on the input provided from an observation of previous fares. The observed data is given as input in the form of a matrix as required to the linear model, and an estimated fare for a specific upcoming flight is calculated.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    A Bayesian Approach for Flight Fare Prediction Based on Kalman Filter


    Beteiligte:


    Erscheinungsdatum :

    10.07.2018


    Format / Umfang :

    13 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    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



    A Prediction of Flight Fare Using K-Nearest Neighbors

    Prasath, S. Naveen / Kumar M, Sathish / Eliyas, Sherin | IEEE | 2022


    Kalman filter approach to traffic modeling and prediction

    Grindey, Gregory J. / Amin, S. M. / Rodin, Ervin Y. et al. | SPIE | 1998