An Incremental Clustering Algorithm with Pattern Drift Detection for IoT-Enabled Smart Grid System

The IoT-enabled smart grid system provides smart meter data for electricity consumers to record their energy consumption behaviors, the typical features of which can be represented by the load patterns extracted from load data clustering. The changeability of consumption behaviors requires load patt...

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Vydané v:	Sensors (Basel, Switzerland) Ročník 21; číslo 19; s. 6466
Hlavní autori:	Jiang, Zigui, Lin, Rongheng, Yang, Fangchun
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland MDPI AG 28.09.2021 MDPI
Predmet:	Algorithms Artificial intelligence Behavior Blockchain Cluster Analysis Clustering Computer Systems Consumers Consumption data stream clustering Distance learning Electricity incremental learning Internet of Things load pattern Machine learning Probability Smart grid technology smart meter data Wavelet transforms data stream clustering incremental learning load pattern smart meter data
ISSN:	1424-8220, 1424-8220
On-line prístup:	Získať plný text
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