Application of probabilistic modeling and machine learning to the diagnosis of FTTH GPON networks

@article{Gosselin2017ApplicationOP,
  title={Application of probabilistic modeling and machine learning to the diagnosis of FTTH GPON networks},
  author={St{\'e}phane Gosselin and Jean-Luc Courant and Serge Romaric Tembo and Sandrine Vaton},
  journal={2017 International Conference on Optical Network Design and Modeling (ONDM)},
  year={2017},
  pages={1-3}
}
This paper presents insights on the promises of probabilistic modeling and machine learning for fault diagnosis in optical access networks. A Bayesian inference engine, called Probabilistic tool for GPON-FTTH Access Network self-DiAgnosis (PANDA), is applied to fault diagnosis of Gigabit capable Passive Optical Networks (GPON). PANDA approach has been assessed on real diagnosis data, showing very satisfactory alignment with an operational rule-based expert system. Furthermore, it provides… CONTINUE READING

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