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.


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    Title :

    A Bayesian Approach for Flight Fare Prediction Based on Kalman Filter


    Contributors:


    Publication date :

    2018-07-10


    Size :

    13 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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