EFFICIENT FAULT LOCATION IN UNDERGROUND DISTRIBUTION SYSTEMS THROUGH OPTIMUM-PATH FOREST
| Contribuinte(s) |
UNIVERSIDADE DE SÃO PAULO |
|---|---|
| Data(s) |
14/10/2013
14/10/2013
2012
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| Resumo |
In this article we propose an efficient and accurate method for fault location in underground distribution systems by means of an Optimum-Path Forest (OPF) classifier. We applied the time domains reflectometry method for signal acquisition, which was further analyzed by OPF and several other well-known pattern recognition techniques. The results indicated that OPF and support vector machines outperformed artificial neural networks and a Bayesian classifier, but OPF was much more efficient than all classifiers for training, and the second fastest for classification. FAPESP [2010/12398-0, 2009/16206-1] FAPESP CNPq [303182/2011-3] CNPq |
| Identificador |
APPLIED ARTIFICIAL INTELLIGENCE, PHILADELPHIA, v. 26, n. 5, supl. 1, Part 1, pp. 503-515, 42370, 2012 0883-9514 http://www.producao.usp.br/handle/BDPI/34389 10.1080/08839514.2012.674289 |
| Idioma(s) |
eng |
| Publicador |
TAYLOR & FRANCIS INC PHILADELPHIA |
| Relação |
APPLIED ARTIFICIAL INTELLIGENCE |
| Direitos |
restrictedAccess Copyright TAYLOR & FRANCIS INC |
| Palavras-Chave | #CLASSIFICATION #NETWORKS #COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE #ENGINEERING, ELECTRICAL & ELECTRONIC |
| Tipo |
article original article publishedVersion |
