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Intelligent decision-making of scheduling for dynamic permutation flowshop via deep reinforcement learning 期刊论文
Sensors (Switzerland), 2021, 卷号: 21, 期号: 3, 页码: 1-20
Authors:  Yang SL(杨圣落);  Xu ZG(徐志刚);  Wang JY(王军义)
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permutation flowshop scheduling problem  deep reinforcement learning  actor-critic  dynamic scheduling  real-time scheduling  new job arrival  tardiness cost  
Brain-Inspired Fast Saliency-Based Filtering Algorithm for Ship Detection in High-Resolution SAR Images 期刊论文
IEEE Transactions on Geoscience and Remote Sensing, 2021, 页码: 1-9
Authors:  Zhang PP(张盼盼);  Luo HB(罗海波);  Ju MR(鞠默然);  He M(何淼);  Chang Z(常铮);  Hui B(惠斌)
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Brain-inspired  deep neural networks (DNNs)  Fast Saliency-based Filtering algorithm (FSF)  filtering mechanisms  priority map  saliency map  
Deep Learning for EMG-based Human-Machine Interaction: A Review 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2021, 卷号: 8, 期号: 3, 页码: 512-533
Authors:  Xiong DZ(熊德臻);  Zhang DH(张道辉);  Zhao XG(赵新刚);  Zhao YW(赵忆文)
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Accuracy  deep learning  electromyography (EMG)  human-machine interaction (HMI)  robustness  
面向机械臂控制的强化学习方法研究 学位论文
博士, 沈阳: 中国科学院沈阳自动化研究所, 2020
Authors:  胡亚洲
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机器人控制  强化学习  值函数近似  优势函数  自由能原理  
基于声发射传感器的工业机器人RV减速器故障诊断问题研究 学位论文
博士, 沈阳: 中国科学院沈阳自动化研究所, 2020
Authors:  安海博
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工业机器人  RV减速器  故障诊断  声发射  健康状态评估  
基于数据驱动的自主式水下潜水器故障检测方法研究与应用 学位论文
硕士, 沈阳: 中国科学院沈阳自动化研究所, 2020
Authors:  杨宗圣
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自主式水下潜水器  故障检测  主元分析  注意力机制  大数据  
基于学习方法的机器人轴孔装配问题研究 学位论文
博士, 沈阳: 中国科学院沈阳自动化研究所, 2020
Authors:  刘乃龙
Adobe PDF(12827Kb)  |  Favorite  |  View/Download:247/28  |  Submit date:2020/06/27
机器人装配  力控制  示教学习  深度强化学习  接触状态  
复杂背景下目标检测与抗干扰跟踪方法研究 学位论文
博士, 沈阳: 中国科学院沈阳自动化研究所, 2020
Authors:  张祥越
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红外末制导  红外小目标检测  抗干扰目标跟踪  相关滤波  卷积神经网络  
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)
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Convolutional neural networks  Empirical mode decomposition  Remaining useful life  Reliability  
Learning Control for Robotic Manipulator with Free Energy 会议论文
Proceedings of the 39th Chinese Control Conference, CCC 2020, Shenyang, China, July 27-29, 2020
Authors:  Hu YZ(胡亚洲);  Wang WX(王文学);  Yu P(于鹏);  Yao C(姚辰);  Liu LQ(刘连庆)
Adobe PDF(176Kb)  |  Favorite  |  View/Download:46/8  |  Submit date:2020/10/10
Evolving Neural Network  Free Energy Principle  Robotic Tracking Control  Reinforcement Learning