These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

126 related items for PubMed ID: 39283188

  • 1. Method for remaining useful life prediction of rolling bearings based on deep reinforcement learning.
    Wang Y, Li Y, Lu H, Wang D.
    Rev Sci Instrum; 2024 Sep 01; 95(9):. PubMed ID: 39283188
    [Abstract] [Full Text] [Related]

  • 2. A Double-Channel Hybrid Deep Neural Network Based on CNN and BiLSTM for Remaining Useful Life Prediction.
    Zhao C, Huang X, Li Y, Yousaf Iqbal M.
    Sensors (Basel); 2020 Dec 11; 20(24):. PubMed ID: 33322457
    [Abstract] [Full Text] [Related]

  • 3. Remaining Useful Life Prediction Based on Adaptive SHRINKAGE Processing and Temporal Convolutional Network.
    Wang H, Yang J, Shi L, Wang R.
    Sensors (Basel); 2022 Nov 23; 22(23):. PubMed ID: 36501790
    [Abstract] [Full Text] [Related]

  • 4. Rolling Bearing Remaining Useful Life Prediction Based on CNN-VAE-MBiLSTM.
    Yang L, Jiang Y, Zeng K, Peng T.
    Sensors (Basel); 2024 May 08; 24(10):. PubMed ID: 38793847
    [Abstract] [Full Text] [Related]

  • 5. Predictive hierarchical reinforcement learning for path-efficient mapless navigation with moving target.
    Li H, Luo B, Song W, Yang C.
    Neural Netw; 2023 Aug 08; 165():677-688. PubMed ID: 37385022
    [Abstract] [Full Text] [Related]

  • 6. Bearing remaining useful life prediction using support vector machine and hybrid degradation tracking model.
    Yan M, Wang X, Wang B, Chang M, Muhammad I.
    ISA Trans; 2020 Mar 08; 98():471-482. PubMed ID: 31492470
    [Abstract] [Full Text] [Related]

  • 7. Approximate Policy-Based Accelerated Deep Reinforcement Learning.
    Wang X, Gu Y, Cheng Y, Liu A, Chen CLP.
    IEEE Trans Neural Netw Learn Syst; 2020 Jun 08; 31(6):1820-1830. PubMed ID: 31398131
    [Abstract] [Full Text] [Related]

  • 8. Long Short-Term Memory Neural Network with Transfer Learning and Ensemble Learning for Remaining Useful Life Prediction.
    Wang L, Liu H, Pan Z, Fan D, Zhou C, Wang Z.
    Sensors (Basel); 2022 Aug 01; 22(15):. PubMed ID: 35957301
    [Abstract] [Full Text] [Related]

  • 9. Remaining Useful Life Prediction Method for Bearings Based on LSTM with Uncertainty Quantification.
    Yang J, Peng Y, Xie J, Wang P.
    Sensors (Basel); 2022 Jun 16; 22(12):. PubMed ID: 35746338
    [Abstract] [Full Text] [Related]

  • 10. Remaining Useful Life Prediction of Rolling Bearings Based on Multi-scale Permutation Entropy and ISSA-LSTM.
    Wang H, Zhang X, Ren M, Xu T, Lu C, Zhao Z.
    Entropy (Basel); 2023 Oct 25; 25(11):. PubMed ID: 37998169
    [Abstract] [Full Text] [Related]

  • 11. Remaining Useful-Life Prediction of the Milling Cutting Tool Using Time-Frequency-Based Features and Deep Learning Models.
    Sayyad S, Kumar S, Bongale A, Kotecha K, Abraham A.
    Sensors (Basel); 2023 Jun 17; 23(12):. PubMed ID: 37420825
    [Abstract] [Full Text] [Related]

  • 12. Deep Learning-Based Remaining Useful Life Estimation of Bearings with Time-Frequency Information.
    Liu B, Gao Z, Lu B, Dong H, An Z.
    Sensors (Basel); 2022 Sep 29; 22(19):. PubMed ID: 36236501
    [Abstract] [Full Text] [Related]

  • 13. Time Series Multiple Channel Convolutional Neural Network with Attention-Based Long Short-Term Memory for Predicting Bearing Remaining Useful Life.
    Jiang JR, Lee JE, Zeng YM.
    Sensors (Basel); 2019 Dec 26; 20(1):. PubMed ID: 31888110
    [Abstract] [Full Text] [Related]

  • 14. Joint optimization of degradation assessment and remaining useful life prediction for bearings with temporal convolutional auto-encoder.
    Ding Y, Jia M, Zhao X, Yan X, Lee CG.
    ISA Trans; 2024 Mar 26; 146():451-462. PubMed ID: 38320915
    [Abstract] [Full Text] [Related]

  • 15. A Cotraining-Based Semisupervised Approach for Remaining-Useful-Life Prediction of Bearings.
    Yan X, Xia X, Wang L, Zhang Z.
    Sensors (Basel); 2022 Oct 13; 22(20):. PubMed ID: 36298116
    [Abstract] [Full Text] [Related]

  • 16. Method for Predicting RUL of Rolling Bearings under Different Operating Conditions Based on Transfer Learning and Few Labeled Data.
    Sun W, Wang H, Liu Z, Qu R.
    Sensors (Basel); 2022 Dec 26; 23(1):. PubMed ID: 36616826
    [Abstract] [Full Text] [Related]

  • 17. A Novel Method for Remaining Useful Life Prediction of Roller Bearings Involving the Discrepancy and Similarity of Degradation Trajectories.
    Luo H, Bo L, Liu X, Zhang H.
    Comput Intell Neurosci; 2021 Dec 26; 2021():2500997. PubMed ID: 34899887
    [Abstract] [Full Text] [Related]

  • 18. Deep deterministic policy gradient algorithm: A systematic review.
    Sumiea EH, Abdulkadir SJ, Alhussian HS, Al-Selwi SM, Alqushaibi A, Ragab MG, Fati SM.
    Heliyon; 2024 May 15; 10(9):e30697. PubMed ID: 38765095
    [Abstract] [Full Text] [Related]

  • 19. Joint Learning of Failure Mode Recognition and Prognostics for Degradation Processes.
    Wang D, Xian X, Song C.
    IEEE Trans Autom Sci Eng; 2024 Apr 15; 21(2):1421-1433. PubMed ID: 38595999
    [Abstract] [Full Text] [Related]

  • 20. Energy saving strategy of cloud data computing based on convolutional neural network and policy gradient algorithm.
    Yang D, Yu J, Du X, He Z, Li P.
    PLoS One; 2022 Apr 15; 17(12):e0279649. PubMed ID: 36584089
    [Abstract] [Full Text] [Related]

    Page: [Next] [New Search]
    of 7.