CLPM: A Cooperative Link Prediction Model for Industrial Internet of Things Using Partitioned Stacked Denoising Autoencoder

With the development of Industry 4.0, an increasing number of industrial Internet of Things (IIoT) mobile devices (MD), which constantly transmit data at any time, are working on the production line. However, due to node movement, signal attenuation, or physical obstacles, data must rely on the tran...

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Veröffentlicht in:	IEEE transactions on industrial informatics Jg. 17; H. 5; S. 3620 - 3629
Hauptverfasser:	Rui, Lanlan, Zhu, Yu, Gao, Zhipeng, Qiu, Xuesong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.05.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Attenuation Deep learning Delays Edge computing Electronic devices Industrial applications Industrial development Industrial Internet of Things Industrial Internet of Things (IIoT) Ions link prediction Noise reduction Prediction models Predictive models Servers stacked denoising autoencoder (SDAE) Task analysis
ISSN:	1551-3203, 1941-0050
Online-Zugang:	Volltext
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