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  • Augmenting a Deferred Bayesian Network with a Genetic Algorithm to Correct Missed RFID Readings

    Author(s)
    Darcy, Peter
    Stantic, Bela
    Sattar, Abdul
    Griffith University Author(s)
    Stantic, Bela
    Sattar, Abdul
    Darcy, Peter J.
    Year published
    2009
    Metadata
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    Abstract
    The alluring promise of a system that would effortlessly identify a mass of objects has been the goal of all research towards Radio Frequency Identification. Unfortunately, in reality, several problems such as missed readings hinder RFID from being as globally utilised as it should be. In this investigation, we present a /emph{Deferred Bayesian Network} solution that has obtained its network configuration through means of /emph{Genetic Algorithm} training. From this research, we have found the optimal amount of chromosomes required to ensure the highest possible result. Additionally, we have compared our methodology ...
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    The alluring promise of a system that would effortlessly identify a mass of objects has been the goal of all research towards Radio Frequency Identification. Unfortunately, in reality, several problems such as missed readings hinder RFID from being as globally utilised as it should be. In this investigation, we present a /emph{Deferred Bayesian Network} solution that has obtained its network configuration through means of /emph{Genetic Algorithm} training. From this research, we have found the optimal amount of chromosomes required to ensure the highest possible result. Additionally, we have compared our methodology with that of a static bayesian network from previous research and have discovered that our trained algorithm yields a cleaner data set result.
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    Conference Title
    Proceedings of the First Malaysian Joint Conference on Artificial Intelligence (MJCAI 2009)
    Publisher URI
    http://www.mimos.my/
    Subject
    Database Management
    Publication URI
    http://hdl.handle.net/10072/31950
    Collection
    • Conference outputs

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