Improved graph-regularized deep belief network with sparse features learning for fault diagnosis-Reference-Cited by-同舟云学术

Improved graph-regularized deep belief network with sparse features learning for fault diagnosis

Published:2022-01-31 Issue:12 Volume:34 Page:9885-9899
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Yang Jie,Bao Weimin,Li Xiaoping,Liu Yanming

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-022-06972-5.pdf

Reference42 articles.

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3. Yu J, Liu G (2020) Knowledge-based deep belief network for machining roughness prediction and knowledge discovery. Comput Ind 121:103262

4. Zuev A, Zhirabok A, Filaretov V (2020) Fault identification in underwater vehicle thrusters via sliding mode observers. Int J Appl Math Comput Sci 30(4):679–688

5. Shao S, McAleer S, Yan R, Baldi P (2019) Highly accurate machine fault diagnosis using deep transfer learning. IEEE Trans Ind Inf 15(4):2446–2455

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