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Energy disaggregation using ensemble of classifiers


Shahriar, S and Rahman, A, Energy disaggregation using ensemble of classifiers, Proceedings, 17-19 April 2013, Sydney, Australia, pp. 161-164. ISBN 978-1-4673-6349-5 (2013) [Conference Extract]

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DOI: doi:10.1109/TENCONSpring.2013.6584433


We study an approach towards energy disaggregation using ensemble of classifiers, a supervised machine learning method. Specifically we identify different appliance loads from the aggregated power usage data. Experimental results on a public data sets show the accuracy of ensemble of classifiers using diverse features in identifying appliance loads.

Item Details

Item Type:Conference Extract
Keywords:energy disaggregation, machine learning methods, data sorting, data sets
Research Division:Information and Computing Sciences
Research Group:Computer vision and multimedia computation
Research Field:Pattern recognition
Objective Division:Information and Communication Services
Objective Group:Other information and communication services
Objective Field:Other information and communication services not elsewhere classified
UTAS Author:Shahriar, S (Dr Sumon Shahriar)
ID Code:116710
Year Published:2013
Deposited By:Information and Communication Technology
Deposited On:2017-05-17
Last Modified:2017-05-17

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