Wear indicator construction for rolling bearings based on an enhanced and unsupervised stacked auto-encoder-Reference-Cited by-同舟云学术

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Wear indicator construction for rolling bearings based on an enhanced and unsupervised stacked auto-encoder

Published:2023-08-18 Issue: Volume: Page:
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Zeng Wenhui,Yu Lisha,Xu Fan^ORCID,Huang Zhelin,Zhou Shengwen,Guo Shunsheng,Du Baigang

Funder

National Natural Science Foundation of China

Guangdong Basic and Applied Basic Research Foundation

Natural Science Foundation of Hubei Province

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s00500-023-09068-x.pdf

Reference32 articles.

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2. Ali A, Zhu YM, Zakarya M (2021a) A data aggregation based approach to exploit dynamic spatio-temporal correlations for citywide crowd flows prediction in fog computing. Multimedia Tools Appl 80(20):31401–31433

3. Ali A, Zhu YM, Zakarya M (2021b) Exploiting dynamic spatio-temporal correlations for citywide traffic flow prediction using attention based neural networks. Inf Sci 577:852–870

4. Ali A, Zhu YM, Zakarya M (2022) Exploiting dynamic spatio-temporal graph convolutional neural networks for citywide traffic flows prediction. Neural Netw 145:233–247

5. Bagordo G, Cazzluani G, Resta F (2011) A modal disturbance estimator for vibration suppression in nonlinear flexible structures, J Sound Vib 330(25):6061–6069

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