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Empirical Mode Decomposition and Temporal Convolutional Networks for Remaining Useful Life Estimation 期刊论文
INTERNATIONAL JOURNAL OF PARALLEL PROGRAMMING, 2020, 卷号: 48, 期号: 1, 页码: 61-79
Authors:  Yang, Wensi;  Yao QF(么庆丰);  Ye KJ(叶可江);  Xu CZ(须成忠)
Adobe PDF(2861Kb)  |  Favorite  |  View/Download:44/9  |  Submit date:2019/11/30
Convolutional neural networks  Empirical mode decomposition  Remaining useful life  Reliability  
Remaining useful life estimation by empirical mode decomposition and ensemble deep convolution neural networks 会议论文
2019 IEEE International Conference on Prognostics and Health Management, ICPHM 2019, San Francisco, CA, United states, June 17-20, 2019
Authors:  Yao QF(么庆丰);  Yang TJ(杨天吉);  Liu Z(刘智);  Zheng ZY(郑泽宇)
View  |  Adobe PDF(1920Kb)  |  Favorite  |  View/Download:32/6  |  Submit date:2019/10/13
Neural Networks  Ensemble Learning  Empirical Mode Decomposition  Remaining Useful Life