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Please use this identifier to cite or link to this item: http://hdl.handle.net/10373/749

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Title: Electricity load profile classification using Fuzzy C-Means method
Authors: Prahastono, Iswan
King, David J.
Özveren, Cüneyt Süheyl
Bradley, David A.
Affiliation: University of Abertay Dundee. School of Computing & Engineering Systems
Keywords: Fuzzy set theory
Load forecasting
Pattern clustering
Issue Date: 2008
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Type: Conference Paper
Refereed: peer-reviewed
Rights: This is the author's final version of this conference paper. Published version (c)IEEE, available from http://dx.doi.org/10.1109/UPEC.2008.4651527
Citation: Prahastono, I., et al. 2008. Electricity load profile classification using Fuzzy C-Means method. In: 43rd International Universities Power Engineering Conference, Padova, 1-4 September 2008. Available from http://dx.doi.org/10.1109/UPEC.2008.4651527
Abstract: This paper presents the Fuzzy C-Means (FCM) clustering method. The FCM technique assigns a degree of membership for each data set to several clusters, thus offering the opportunity to deal with load profiles that could belong to more than one group at the same time. The FCM algorithm is based on minimising a c-means objective function to determine an optimal classification. The simulation of FCM was carried out using actual sample data from Indonesia and the results are presented. Some validity index measurements was carried out to estimate the compactness of the resulting clusters or to find the optimal number of clusters for a data set.
URI: http://hdl.handle.net/10373/749
ISBN: 9781424432943
Appears in Collections:Computing & Engineering Systems Collection

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