Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/1450
Título: Data mining techniques to support the classification of MV electricity customers
Autor: Ramos, Sérgio
Vale, Zita
Palavras-chave: Typical load profile
Clustering
Data mining
Classification
Consumer classes
Data: 2008
Editora: IEEE
Resumo: This paper describes a methodology that was developed for the classification of Medium Voltage (MV) electricity customers. Starting from a sample of data bases, resulting from a monitoring campaign, Data Mining (DM) techniques are used in order to discover a set of a MV consumer typical load profile and, therefore, to extract knowledge regarding to the electric energy consumption patterns. In first stage, it was applied several hierarchical clustering algorithms and compared the clustering performance among them using adequacy measures. In second stage, a classification model was developed in order to allow classifying new consumers in one of the obtained clusters that had resulted from the previously process. Finally, the interpretation of the discovered knowledge are presented and discussed.
URI: http://hdl.handle.net/10400.22/1450
ISBN: 978-1-4244-1905-0
978-1-4244-1906-7
ISSN: 1932-5517
Versão do Editor: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4596669
Aparece nas colecções:ISEP – GECAD – Comunicações em eventos científicos

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