Please use this identifier to cite or link to this item:
- EFFICIENT FAULT LOCATION IN UNDERGROUND DISTRIBUTION SYSTEMS THROUGH OPTIMUM-PATH FOREST
- Universidade de São Paulo (USP)
- Universidade Estadual Paulista (UNESP)
- Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
- Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
- FAPESP: 10/12398-0
- FAPESP: 09/16206-1
- CNPq: 303182/2011-3
- 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.
- Applied Artificial Intelligence. Philadelphia: Taylor & Francis Inc, v. 26, n. 5, p. 503-515, 2012.
- Taylor & Francis Inc
- Acesso restrito
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.