ABSTRACT
Line test data is important for identifying and locating faults in access networks. However, the complexity of the data makes devising suitable evaluation heuristics difficult. This paper describes the use of a neural network, trained using historical data, both as a stand-alone system and as a pre-processor for a rule-based expert system. Comparisons between the different cases are drawn and recommendations are made for the applicability of the different approaches.
