Global telecommunication systems are built with extensive redundancy and complex management systems to ensure robustness.
Fault identification and management of this complexity is an ops research issue with which data mining can greatly assist.
This paper proposes a hybrid data mining architecture and a parallel genetic algorithm (PGA) applied to the mining of Bayesian
Belief Networks (BBN) from Telecommunication Management Network (TMN) data.