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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

115 related articles for article (PubMed ID: 38821997)

  • 1. An interpretable online prediction method for remaining useful life of lithium-ion batteries.
    Li Z; Shen S; Ye Y; Cai Z; Zhen A
    Sci Rep; 2024 May; 14(1):12541. PubMed ID: 38821997
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Remaining Useful Life Prediction for Lithium-Ion Batteries Based on Gaussian Processes Mixture.
    Li L; Wang P; Chao KH; Zhou Y; Xie Y
    PLoS One; 2016; 11(9):e0163004. PubMed ID: 27632176
    [TBL] [Abstract][Full Text] [Related]  

  • 3. XGBoost-Based Remaining Useful Life Estimation Model with Extended Kalman Particle Filter for Lithium-Ion Batteries.
    Jafari S; Byun YC
    Sensors (Basel); 2022 Dec; 22(23):. PubMed ID: 36502223
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A Hybrid Data-Driven Approach for Multistep Ahead Prediction of State of Health and Remaining Useful Life of Lithium-Ion Batteries.
    Ali MU; Zafar A; Masood H; Kallu KD; Khan MA; Tariq U; Kim YJ; Chang B
    Comput Intell Neurosci; 2022; 2022():1575303. PubMed ID: 35733564
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Early prediction of remaining useful life for lithium-ion batteries based on CEEMDAN-transformer-DNN hybrid model.
    Cai Y; Li W; Zahid T; Zheng C; Zhang Q; Xu K
    Heliyon; 2023 Jul; 9(7):e17754. PubMed ID: 37456048
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Prognostics of Lithium-Ion Batteries Based on Wavelet Denoising and DE-RVM.
    Zhang C; He Y; Yuan L; Xiang S; Wang J
    Comput Intell Neurosci; 2015; 2015():918305. PubMed ID: 26413090
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A Hybrid Data Preprocessing-Based Hierarchical Attention BiLSTM Network for Remaining Useful Life Prediction of Spacecraft Lithium-Ion Batteries.
    Luo T; Liu M; Shi P; Duan G; Cao X
    IEEE Trans Neural Netw Learn Syst; 2023 Sep; PP():. PubMed ID: 37725745
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A Novel Remaining Useful Life Prediction Method for Capacity Diving Lithium-Ion Batteries.
    Gao K; Xu J; Li Z; Cai Z; Jiang D; Zeng A
    ACS Omega; 2022 Aug; 7(30):26701-26714. PubMed ID: 35936419
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A remaining useful life estimation method based on long short-term memory and federated learning for electric vehicles in smart cities.
    Chen X; Chen Z; Zhang M; Wang Z; Liu M; Fu M; Wang P
    PeerJ Comput Sci; 2023; 9():e1652. PubMed ID: 38077580
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Life Prediction of Battery Using a Neural Gaussian Process with Early Discharge Characteristics.
    Yin A; Tan Z; Tan J
    Sensors (Basel); 2021 Feb; 21(4):. PubMed ID: 33562499
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A fusion framework for lithium-ion batteries state of health estimation using compressed sensing and entropy weight method.
    He N; Qian C; Shen C; Huangfu Y
    ISA Trans; 2023 Apr; 135():585-604. PubMed ID: 36347758
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Improved Battery Cycle Life Prediction Using a Hybrid Data-Driven Model Incorporating Linear Support Vector Regression and Gaussian.
    Alipour M; Tavallaey SS; Andersson AM; Brandell D
    Chemphyschem; 2022 Apr; 23(7):e202100829. PubMed ID: 35075749
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Remaining Useful Life Prediction of Lithium-Ion Batteries Using Neural Networks with Adaptive Bayesian Learning.
    Pugalenthi K; Park H; Hussain S; Raghavan N
    Sensors (Basel); 2022 May; 22(10):. PubMed ID: 35632212
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Remaining capacity estimation of lithium-ion batteries based on the constant voltage charging profile.
    Wang Z; Zeng S; Guo J; Qin T
    PLoS One; 2018; 13(7):e0200169. PubMed ID: 29979778
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A novel gear RUL prediction method by diffusion model generation health index and attention guided multi-hierarchy LSTM.
    Chen X
    Sci Rep; 2024 Jan; 14(1):1795. PubMed ID: 38245612
    [TBL] [Abstract][Full Text] [Related]  

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

  • 17. Multi-Fractal Weibull Adaptive Model for the Remaining Useful Life Prediction of Electric Vehicle Lithium Batteries.
    Deng W; Gao Y; Chen J; Kudreyko A; Cattani C; Zio E; Song W
    Entropy (Basel); 2023 Apr; 25(4):. PubMed ID: 37190434
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A simulation-driven prediction model for state of charge estimation of electric vehicle lithium battery.
    Zhang J; Song C; Xiang J
    Heliyon; 2024 May; 10(10):e30988. PubMed ID: 38770289
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Prognostics for lithium-ion batteries using a two-phase gamma degradation process model.
    Lin CP; Ling MH; Cabrera J; Yang F; Yu DYW; Tsui KL
    Reliab Eng Syst Saf; 2021 Oct; 214():. PubMed ID: 34305335
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Hybrid Degradation Equipment Remaining Useful Life Prediction Oriented Parallel Simulation considering Model Soft Switch.
    Ge C; Zhu Y; Di Y
    Comput Intell Neurosci; 2019; 2019():9179870. PubMed ID: 30992700
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.