Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/1480
Título: Power systems reliability calculation based on fuzzy data mining
Autor: Ramos, Sérgio
Khodr, H. M.
Azevedo, Filipe
Vale, Zita
Palavras-chave: Data mining
Knowledge discovery
Fuzzy logic
Monte Carlo
Power system maintenance
Data: 2009
Editora: IEEE
Resumo: This paper presents a methodology supported on the data base knowledge discovery process (KDD), in order to find out the failure probability of electrical equipments’, which belong to a real electrical high voltage network. Data Mining (DM) techniques are used to discover a set of outcome failure probability and, therefore, to extract knowledge concerning to the unavailability of the electrical equipments such us power transformers and high-voltages power lines. The framework includes several steps, following the analysis of the real data base, the pre-processing data, the application of DM algorithms, and finally, the interpretation of the discovered knowledge. To validate the proposed methodology, a case study which includes real databases is used. This data have a heavy uncertainty due to climate conditions for this reason it was used fuzzy logic to determine the set of the electrical components failure probabilities in order to reestablish the service. The results reflect an interesting potential of this approach and encourage further research on the topic.
URI: http://hdl.handle.net/10400.22/1480
ISBN: 978-1-4244-4241-6
ISSN: 1944-9925
Versão do Editor: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5275783&tag=1
Aparece nas colecções:ISEP – GECAD – Comunicações em eventos científicos

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