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Conference Papers Year : 2012

Optimization of fault diagnosis based on the combination of Bayesian Networks and case Based Reasoning

L. Bennacer
  • Function : Author
L. Ciavaglia
  • Function : Author
A. A. Chibani
  • Function : Author
Yacine Y. Amirat
A Mellouk
  • Function : Author
CIR

Abstract

Fault diagnosis is one of the most important tasks in fault management. The main objective of the fault management system is to detect and localize failures as soon as they occur to minimize their effects on the network performance and therefore on the service quality perceived by users. In this paper, we present a new hybrid approach that combines Bayesian Networks and Case-Based Reasoning to overcome the usual limits of fault diagnosis techniques and reduce human intervention in this process. The proposed mechanism allows identifying the root cause failure with a finer precision and high reliability while reducing the process computation time and taking into account the network dynamicity.
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Dates and versions

hal-01678616 , version 1 (09-01-2018)

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  • HAL Id : hal-01678616 , version 1

Cite

L. Bennacer, L. Ciavaglia, A. A. Chibani, Yacine Y. Amirat, A Mellouk. Optimization of fault diagnosis based on the combination of Bayesian Networks and case Based Reasoning. Proc. Of the IEEE/IFIP Network Operations and Management Symposium (NOMS), Apr 2012, Hawaii, USA, United States. pp.619-622. ⟨hal-01678616⟩

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