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 *

162 related articles for article (PubMed ID: 34764604)

  • 1. A novel general-purpose hybrid model for time series forecasting.
    Yang Y; Fan C; Xiong H
    Appl Intell (Dordr); 2022; 52(2):2212-2223. PubMed ID: 34764604
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Carbon price forecasting based on modified ensemble empirical mode decomposition and long short-term memory optimized by improved whale optimization algorithm.
    Yang S; Chen D; Li S; Wang W
    Sci Total Environ; 2020 May; 716():137117. PubMed ID: 32074939
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A novel model based on CEEMDAN, IWOA, and LSTM for ultra-short-term wind power forecasting.
    Yang S; Yuan A; Yu Z
    Environ Sci Pollut Res Int; 2023 Jan; 30(5):11689-11705. PubMed ID: 36098919
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Load forecasting method based on CEEMDAN and TCN-LSTM.
    Heng L; Hao C; Nan LC
    PLoS One; 2024; 19(7):e0300496. PubMed ID: 38968242
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Temperature Prediction of Seasonal Frozen Subgrades Based on CEEMDAN-LSTM Hybrid Model.
    Chen L; Liu X; Zeng C; He X; Chen F; Zhu B
    Sensors (Basel); 2022 Aug; 22(15):. PubMed ID: 35957299
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Short-term wind speed forecasting based on a hybrid model of ICEEMDAN, MFE, LSTM and informer.
    Xinxin W; Xiaopan S; Xueyi A; Shijia L
    PLoS One; 2023; 18(9):e0289161. PubMed ID: 37682883
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A new denoising approach based on mode decomposition applied to the stock market time series: 2LE-CEEMDAN.
    Akşehir ZD; Kılıç E
    PeerJ Comput Sci; 2024; 10():e1852. PubMed ID: 38435596
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Integration of complete ensemble empirical mode decomposition with deep long short-term memory model for particulate matter concentration prediction.
    Fu M; Le C; Fan T; Prakapovich R; Manko D; Dmytrenko O; Lande D; Shahid S; Yaseen ZM
    Environ Sci Pollut Res Int; 2021 Dec; 28(45):64818-64829. PubMed ID: 34318419
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Empirical mode decomposition based long short-term memory neural network forecasting model for the short-term metro passenger flow.
    Chen Q; Wen D; Li X; Chen D; Lv H; Zhang J; Gao P
    PLoS One; 2019; 14(9):e0222365. PubMed ID: 31509599
    [TBL] [Abstract][Full Text] [Related]  

  • 10. An AQI decomposition ensemble model based on SSA-LSTM using improved AMSSA-VMD decomposition reconstruction technique.
    Wang K; Fan X; Yang X; Zhou Z
    Environ Res; 2023 Sep; 232():116365. PubMed ID: 37301497
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Gas Concentration Prediction Based on IWOA-LSTM-CEEMDAN Residual Correction Model.
    Xu N; Wang X; Meng X; Chang H
    Sensors (Basel); 2022 Jun; 22(12):. PubMed ID: 35746193
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A prediction model of aquaculture water quality based on multiscale decomposition.
    Yang H; Liu S
    Math Biosci Eng; 2021 Sep; 18(6):7561-7579. PubMed ID: 34814263
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Zoonotic outbreak risk prediction with long short-term memory models: a case study with schistosomiasis, echinococcosis, and leptospirosis.
    Chen C; He Z; Zhao J; Zhu X; Li J; Wu X; Chen Z; Chen H; Jia G
    BMC Infect Dis; 2024 Sep; 24(1):1062. PubMed ID: 39333964
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A four-stage hybrid model for hydrological time series forecasting.
    Di C; Yang X; Wang X
    PLoS One; 2014; 9(8):e104663. PubMed ID: 25111782
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A Solar Irradiance Forecasting Framework Based on the CEE-WGAN-LSTM Model.
    Li Q; Zhang D; Yan K
    Sensors (Basel); 2023 Mar; 23(5):. PubMed ID: 36905005
    [TBL] [Abstract][Full Text] [Related]  

  • 16. An Improved STL-LSTM Model for Daily Bus Passenger Flow Prediction during the COVID-19 Pandemic.
    Jiao F; Huang L; Song R; Huang H
    Sensors (Basel); 2021 Sep; 21(17):. PubMed ID: 34502841
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A Deep Learning Model with Signal Decomposition and Informer Network for Equipment Vibration Trend Prediction.
    Wang H; Guo M; Tian L
    Sensors (Basel); 2023 Jun; 23(13):. PubMed ID: 37447674
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Stock Index Prediction Based on Time Series Decomposition and Hybrid Model.
    Lv P; Wu Q; Xu J; Shu Y
    Entropy (Basel); 2022 Jan; 24(2):. PubMed ID: 35205442
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A novel model for runoff prediction based on the ICEEMDAN-NGO-LSTM coupling.
    Yang C; Jiang Y; Liu Y; Liu S; Liu F
    Environ Sci Pollut Res Int; 2023 Jul; 30(34):82179-82188. PubMed ID: 37318729
    [TBL] [Abstract][Full Text] [Related]  

  • 20. LSTM Short-Term Wind Power Prediction Method Based on Data Preprocessing and Variational Modal Decomposition for Soft Sensors.
    Lei P; Ma F; Zhu C; Li T
    Sensors (Basel); 2024 Apr; 24(8):. PubMed ID: 38676138
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.