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Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction

In a world of connectivity empowered by the advancement of the Internet of Things (IoT), an infinite number of data streams have emerged. Thus, data stream clustering is crucial for extracting hidden knowledge and data mining. Various data stream clustering methods have lately been introduced. Yet,...

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Bibliographic Details
Main Authors: Alkawsi G., Al-amri R., Baashar Y., Ghorashi S., Alabdulkreem E., Kiong Tiong S.
Other Authors: 57191982354
Format: Article
Published: Elsevier B.V. 2024
Subjects:
Anomaly detection
Clustering
Computational power
Data stream
Entropy
High-dimensionality
IoT
Cluster analysis
Clustering algorithms
Data mining
Internet of things
Petroleum reservoir evaluation
% reductions
Clustering methods
Clusterings
Data stream clustering
High dimensionality
High-dimensional data streams
Reduction algorithms
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