In this paper we present a Bayesian Network for faultdiagnosis used in an industrial tanks system. We obtain theBayesian Network first and later based on this, we build adefined structure as Junction Tree. This tree is where wespread the probabilities with the algorithm known as LAZY-AR(also Junction Tree). Nowadays the state of the art ininference algorithms in Bayesian Networks is the JunctionTree algorithm. We prove empirically through a case studyas the Junction Tree algorithm has better performance withregard to the traditional algorithms as the Polytree.


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    Title :

    Fault Diagnosis in an Industrial Process Using Bayesian Networks: Application of the Junction Tree Algorithm


    Contributors:


    Publication date :

    2009-09-01


    Size :

    614649 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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