Roller bearing fault diagnosis using stacked denoising autoencoder in deep learning and Gath–Geva clustering algorithm without principal component analysis and data label

标题
Roller bearing fault diagnosis using stacked denoising autoencoder in deep learning and Gath–Geva clustering algorithm without principal component analysis and data label
作者
关键词
Deep learning, Stacked denoising autoencoder, Gath–Geva clustering algorithm, Roller bearing fault diagnosis
出版物
APPLIED SOFT COMPUTING
Volume 73, Issue -, Pages 898-913
出版商
Elsevier BV
发表日期
2018-10-05
DOI
10.1016/j.asoc.2018.09.037

向作者/读者发起求助以获取更多资源

Reprint

联系作者

Find Funding. Review Successful Grants.

Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.

Explore

Discover Peeref hubs

Discuss science. Find collaborators. Network.

Join a conversation