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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|
|Issue Date: ||2008|
|Publisher: ||Institute of Electrical and Electronics Engineers (IEEE)|
|Type: ||Conference Paper|
|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.|
|Appears in Collections:||Computing & Engineering Systems Collection|
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