Road accident data analysis using Bayesian networks

Bayesian Networks (BNs) are graphical probabilistic models representing the joint probability function over a set of random variables using a directed acyclic graphical structure. In this paper, the authors consider a road accident data set collected at one of the popular highways in Iran. Implementing the well-known parents and children algorithm, as a constraint-based approach, the authors construct a BN model for the available accident data. Once the structure of the BN is learnt, the authors concentrate on the parameter-learning task. They compute the maximum-likelihood estimates of some parameters of interest, specifically, conditional probability of fatalities in the network.

Language

  • English

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  • Accession Number: 01667015
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Apr 4 2018 3:11PM