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 *

177 related articles for article (PubMed ID: 36559997)

  • 21. Intra-Day Solar Power Forecasting Strategy for Managing Virtual Power Plants.
    Moreno G; Santos C; Martín P; Rodríguez FJ; Peña R; Vuksanovic B
    Sensors (Basel); 2021 Aug; 21(16):. PubMed ID: 34451090
    [TBL] [Abstract][Full Text] [Related]  

  • 22. A novel hybrid learning paradigm with feature extraction for carbon price prediction based on Bi-directional long short-term memory network optimized by an improved sparrow search algorithm.
    Zhou J; Xu Z; Wang S
    Environ Sci Pollut Res Int; 2022 Sep; 29(43):65585-65598. PubMed ID: 35488159
    [TBL] [Abstract][Full Text] [Related]  

  • 23. [Research on mild cognitive impairment diagnosis based on Bayesian optimized long-short-term neural network model].
    Li X; Li Z; Liu Y; Su R; Xu Y; Jing J; Yin L
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2023 Jun; 40(3):450-457. PubMed ID: 37380383
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Multi-Input Deep Convolutional Neural Network Model for Short-Term Power Prediction of Photovoltaics.
    Zhang H; Zhao Y; Kang H; Mei E; Han H
    Comput Intell Neurosci; 2022; 2022():9350169. PubMed ID: 36177316
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Variational mode decomposition combined fuzzy-Twin support vector machine model with deep learning for solar photovoltaic power forecasting.
    Balraj G; Victoire AA; S J; Victoire A
    PLoS One; 2022; 17(9):e0273632. PubMed ID: 36112635
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Artificial Intelligence based accurately load forecasting system to forecast short and medium-term load demands.
    Butt FM; Hussain L; Mahmood A; Lone KJ
    Math Biosci Eng; 2020 Dec; 18(1):400-425. PubMed ID: 33525099
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Passenger Flow Forecasting in Metro Transfer Station Based on the Combination of Singular Spectrum Analysis and AdaBoost-Weighted Extreme Learning Machine.
    Zhou W; Wang W; Zhao D
    Sensors (Basel); 2020 Jun; 20(12):. PubMed ID: 32585963
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Sensorless PV Power Forecasting in Grid-Connected Buildings through Deep Learning.
    Son J; Park Y; Lee J; Kim H
    Sensors (Basel); 2018 Aug; 18(8):. PubMed ID: 30072641
    [TBL] [Abstract][Full Text] [Related]  

  • 29. A Two-Stage Multistep-Ahead Electricity Load ForecastingScheme Based on LightGBM and Attention-BiLSTM.
    Park J; Hwang E
    Sensors (Basel); 2021 Nov; 21(22):. PubMed ID: 34833791
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Forecasting Teleconsultation Demand Using an Ensemble CNN Attention-Based BILSTM Model with Additional Variables.
    Chen W; Li J
    Healthcare (Basel); 2021 Aug; 9(8):. PubMed ID: 34442130
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Monthly runoff prediction based on a coupled VMD-SSA-BiLSTM model.
    Zhang X; Wang X; Li H; Sun S; Liu F
    Sci Rep; 2023 Aug; 13(1):13149. PubMed ID: 37573389
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Hyperparameter Optimization of Bayesian Neural Network Using Bayesian Optimization and Intelligent Feature Engineering for Load Forecasting.
    Zulfiqar M; Gamage KAA; Kamran M; Rasheed MB
    Sensors (Basel); 2022 Jun; 22(12):. PubMed ID: 35746227
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Deep belief rule based photovoltaic power forecasting method with interpretability.
    Han P; He W; Cao Y; Li Y; Zhang Y
    Sci Rep; 2022 Aug; 12(1):14467. PubMed ID: 36002587
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Deep learning-driven hybrid model for short-term load forecasting and smart grid information management.
    Wen X; Liao J; Niu Q; Shen N; Bao Y
    Sci Rep; 2024 Jun; 14(1):13720. PubMed ID: 38877081
    [TBL] [Abstract][Full Text] [Related]  

  • 35. A new hybrid model for photovoltaic output power prediction.
    Zou J; Wei M; Song Q; Zhou Z
    Environ Sci Pollut Res Int; 2023 Dec; 30(58):122934-122957. PubMed ID: 37980325
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Increasing the Accuracy of Hourly Multi-Output Solar Power Forecast with Physics-Informed Machine Learning.
    Pombo DV; Bindner HW; Spataru SV; Sørensen PE; Bacher P
    Sensors (Basel); 2022 Jan; 22(3):. PubMed ID: 35161500
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Deep learning-based neural networks for day-ahead power load probability density forecasting.
    Zhou Y; Zhu D; Chen H; Guo S; Xu CY; Chang FJ
    Environ Sci Pollut Res Int; 2023 Feb; 30(7):17741-17764. PubMed ID: 36201077
    [TBL] [Abstract][Full Text] [Related]  

  • 38. 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]  

  • 39. Multi-step interval prediction of ultra-short-term wind power based on CEEMDAN-FIG and CNN-BiLSTM.
    Zhao Z; Nan H; Liu Z; Yu Y
    Environ Sci Pollut Res Int; 2022 Aug; 29(38):58097-58109. PubMed ID: 35362890
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Modeling Bitcoin Prices using Signal Processing Methods, Bayesian Optimization, and Deep Neural Networks.
    Tripathi B; Sharma RK
    Comput Econ; 2022 Oct; ():1-27. PubMed ID: 36337302
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 9.