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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)
Adobe PDF(1920Kb)  |  Favorite  |  View/Download：85/21  |  Submit date：2019/10/13
Neural Networks  Ensemble Learning  Empirical Mode Decomposition  Remaining Useful Life  
Replacement and inventory control for a multi-customer product service system with decreasing replacement costs 期刊论文
European Journal of Operational Research, 2019, 卷号: 273, 期号: 2, 页码: 561-574
Authors:  Liu XB(刘心报);  Yang TJ(杨天吉);  Pei J(裴军);  Liao, Haitao;  Pohl, Edward A.
Adobe PDF(1903Kb)  |  Favorite  |  View/Download：190/51  |  Submit date：2018/09/30
Or In Service Industries  Production Service System  Replacement Policies  Inventory Control