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A Bayesian Approach for Flight Fare Prediction Based on Kalman Filter

  • Abhijit Boruah
  • Kamal Baruah
  • Biman Das
  • Manash Jyoti Das
  • Niranjan Borpatra Gohain
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 714)

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.

Keywords

Flight fare Observation Prediction Kalman filter Linear model 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Abhijit Boruah
    • 1
  • Kamal Baruah
    • 1
  • Biman Das
    • 1
  • Manash Jyoti Das
    • 1
  • Niranjan Borpatra Gohain
    • 1
  1. 1.Department of Computer Science and EngineeringDUIET, Dibrugarh UniversityDibrugarhIndia

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