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Representational learning for fault diagnosis of wind turbine equipment: A multi-layered extreme learning machines approach Journal article
Energies, 2016,Volume: 9,Issue: 6
作者:  Yang Z.-X.;  Wang X.-B.;  Zhong J.-H.
收藏  |  浏览/下载:2/0  |  提交时间:2018/12/22
Autoencoder (Ae)  Classification  Extreme Learning Machines (Elm)  Fault Diagnosis  Wind Turbine  
Optimize real-valued RBM with Bidirectional Autoencoder Conference paper
iFUZZY 2015 - 2015 International Conference on Fuzzy Theory and Its Applications, Conference Digest, Yilan, TAIWAN, NOV 18-20, 2015
作者:  Feng Q.;  Chen L.;  Chen C.L.P.
收藏  |  浏览/下载:3/0  |  提交时间:2019/02/11
Back Propagation  Bidirectional Autoencoder  Rbm Optimization  Sgd  
Exploiting Rich Feature Representation for SMT N-Best Reranking Conference paper
PROCEEDINGS OF 2016 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION (ICWAPR), Jeju, SOUTH KOREA, JUL 10-13, 2016
作者:  Tong, Yu;  Derek F. Wong;  Lidia S. Chao
收藏  |  浏览/下载:1/0  |  提交时间:2019/04/25
N-best Reranking  Syntactic Features  Semantic Features  Deep Neural Networks