Smart power consumption abnormality detection in buildings using micromoments and improved K‐nearest neighbors

Anomaly detection in energy consumption is a crucial step towards developing efficient energy saving systems, diminishing overall energy expenditure and reducing carbon emissions. Therefore, implementing powerful techniques to identify anomalous consumption in buildings and providing this informatio...

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Bibliographic Details

Published in:	International journal of intelligent systems Vol. 36; no. 6; pp. 2865 - 2894
Main Authors:	Himeur, Yassine, Alsalemi, Abdullah, Bensaali, Faycal, Amira, Abbes
Format:	Journal Article
Language:	English
Published:	New York John Wiley & Sons, Inc 01.06.2021
Subjects:	Abnormalities Algorithms Anomalies anomaly detection Buildings Datasets Energy consumption improved K‐nearest neighbors Intelligent systems Machine learning micromoments one‐class support vector machine Power consumption rule‐based algorithm Support vector machines
ISSN:	0884-8173, 1098-111X
Online Access:	Get full text
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