Locating Faults in Tree-Structured Networks
Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence. Diagnosis and Qualitative Reasoning. Pages 434-438.
Abstract
An important problem in fault diagnosis is how to locate faulty components by analysing performance measurements from those components. In this paper, we present an algorithm that uses the informationtheoretic Minimum Message Length (MML) principle to locate faults in tree-structured networks. Treestructured networks are an important application for fault diagnosis due to their use as distribution networks in telecommunication and power industries. The main advantage of using a MML approach is that we can model both the complexity of an explanation for a set of measurements, as well as the accuracy of the explanation. We demonstrate the effectiveness of this approach through an empirical evaluation on a range of simulated data.
@inproceedings{ijcai1997p64,
title = {Locating Faults in Tree-Structured Networks},
author = {Leckie, Christopher and Dale, Michael},
booktitle = {Proceedings of the Fifteenth International Joint Conference on
Artificial Intelligence, {IJCAI-97}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Martha E. Pollack},
pages = {434--438},
year = {1997},
note = {Diagnosis and Qualitative Reasoning},
url = {https://ijcai.org/proceedings/1997/64},
}
TY - CPAPER TI - Locating Faults in Tree-Structured Networks AU - Leckie, Christopher AU - Dale, Michael T2 - Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, IJCAI-97 PB - International Joint Conferences on Artificial Intelligence PY - 1997 SP - 434 EP - 438 UR - https://ijcai.org/proceedings/1997/64 ER -Copied
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