• International Journal of Technology (IJTech)
  • Vol 6, No 6 (2015)

Bayesian Mixture Model for Prediction of Bus Arrival Time

Bayesian Mixture Model for Prediction of Bus Arrival Time

Title: Bayesian Mixture Model for Prediction of Bus Arrival Time
Misbahuddin , Riri Fitri Sari

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Published at : 30 Dec 2015
Volume : IJtech Vol 6, No 6 (2015)
DOI : https://doi.org/10.14716/ijtech.v6i6.1350

Cite this article as:

Misbahuddin, Sari, R.F., 2015. Bayesian Mixture Model for Prediction of Bus Arrival Time. International Journal of Technology. Volume 6(6), pp. 961-970



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Misbahuddin Department of Electrical Engineering, Faculty of Engineering, University of Indonesia, Kampus UI Depok, Depok 16424, Indonesia
Riri Fitri Sari Department of Electrical Engineering, Faculty of Engineering, University of Indonesia, Kampus UI Depok, Depok 16424, Indonesia
Email to Corresponding Author

Abstract
Bayesian Mixture Model for Prediction of Bus Arrival Time

Providing travelers with accurate bus arrival time is an essential need to plan their traveling and reduce long waiting time for buses. In this paper, we proposed a new approach based on a Bayesian mixture model for the prediction. The Gaussian mixture model (GMM) was used as the joint probability density function of the Bayesian network to formulate the conditional probability. Furthermore, the Expectation maximization (EM) Algorithm was also used to estimate the new parameters of the GMM through an iterative method to obtain the maximum likelihood estimation (MLE) as a convergence of the algorithm. The performance of the prediction model was tested in the bus lanes in the University of Indonesia. The results show that the model can be a potential model to predict effectively the bus arrival time.

Arrival time prediction, Bayesian network, Gaussian mixture model

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