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A method for degradation prediction based on Hidden Semi-Markov models with mixture of Kernels 期刊论文
Computers in Industry, 2020, 卷号: 122, 页码: 1-13
Authors:  Yang TJ(杨天吉);  Zheng ZY(郑泽宇);  Qi L(亓亮)
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Prognostics and health management  Remaining useful lifetime  Hidden semi-Markov models  Kernel method approximationa  
Path Planning Method With Improved Artificial Potential Field-A Reinforcement Learning Perspective 期刊论文
IEEE ACCESS, 2020, 卷号: 8, 页码: 135513-135523
Authors:  Yao QF(么庆丰);  Zheng ZY(郑泽宇);  Qi, Liang;  Yuan, Haitao;  Guo, Xiwang;  Zhao M(赵明);  Liu Z(刘智);  Yang TJ(杨天吉)
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Path planning  Learning (artificial intelligence)  Gravity  Potential energy  Mobile agents  Real-time systems  Reinforcement learning  neural network  potential field  path planning  
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)
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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.
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Or In Service Industries  Production Service System  Replacement Policies  Inventory Control