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Fault Diagnosis Based on Non-Negative Sparse Constrained Deep Neural Networks and Dempster–Shafer Theory

机译：基于非负稀疏约束深度神经网络和Dempster-Shafer理论的故障诊断

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Zhuo Zhang; Wen Jiang; Jie Geng; Xinyang Deng; Xiang Li;
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1. Fault Diagnosis Based on Non-Negative Sparse Constrained Deep Neural Networks and Dempster–Shafer Theory [J] . Zhang Zhuo, Jiang Wen, Geng Jie, Quality Control, Transactions . 2020,第期

机译：基于非负稀疏约束深度神经网络和Dempster-Shafer理论的故障诊断
2. A bearing fault and severity diagnostic technique using adaptive deep belief networks and Dempster-Shafer theory [J] . Yu Kun, Lin Tian Ran, Tan Jiwen Structural health monitoring . 2020,第1期

机译：基于自适应深度信念网络和Dempster-Shafer理论的轴承故障和严重性诊断技术
3. Run-to-run failure detection and diagnosis using neural networks and Dempster-Shafer theory: an application to excimer laser ablation [J] . Setia R., May G.S. IEEE transactions on electronics packaging manufacturing . 2006,第1期

机译：使用神经网络和Dempster-Shafer理论进行的运行间故障检测和诊断：准分子激光烧蚀的应用
4. Deep Belief Network and Dempster-Shafer Evidence Theory for Bearing Fault Diagnosis [C] . Duy Tang Hoang, Hee Jun Kang IEEE International Symposium on Industrial Electronics . 2018

机译：轴承故障诊断的深信度网络和Dempster-Shafer证据理论
5. Development of Novel Computational Algorithms for Localization in Wireless Sensor Networks through Incorporation of Dempster-Shafer Evidence Theory [D] . Elkin, Colin P. 2015

机译：结合Dempster-Shafer证据理论开发无线传感器网络中的新型计算算法
6. Bearing Fault Diagnosis Based on a Hybrid Classifier Ensemble Approach and the Improved Dempster-Shafer Theory [O] . Yanxue Wang, Fang Liu, Aihua Zhu 2019

机译：基于混合分类器集成和改进的Dempster-Shafer理论的轴承故障诊断
7. Bearing Fault Diagnosis Based on a Hybrid Classifier Ensemble Approach and the Improved Dempster-Shafer Theory [O] . Yanxue Wang, Fang Liu, Aihua Zhu 2019

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8. Dempster-Shafer Fusion for Personnel Detection: Application of Dempster-Shafer Theory with Ultrasonic Micro-Doppler and PIR Sensors. [R] . Maguire, B., Desai, S. 2012

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Fault Diagnosis Based on Non-Negative Sparse Constrained Deep Neural Networks and Dempster–Shafer Theory

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