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 *

467 related articles for article (PubMed ID: 34335724)

  • 41. Research on machine learning hybrid framework by coupling grid-based runoff generation model and runoff process vectorization for flood forecasting.
    Liu C; Xie T; Li W; Hu C; Jiang Y; Li R; Song Q
    J Environ Manage; 2024 Jul; 364():121466. PubMed ID: 38870784
    [TBL] [Abstract][Full Text] [Related]  

  • 42. Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data.
    Kim T; Kim HY
    PLoS One; 2019; 14(2):e0212320. PubMed ID: 30768647
    [TBL] [Abstract][Full Text] [Related]  

  • 43. Stepwise decomposition-integration-prediction framework for runoff forecasting considering boundary correction.
    Xu Z; Mo L; Zhou J; Fang W; Qin H
    Sci Total Environ; 2022 Dec; 851(Pt 2):158342. PubMed ID: 36037902
    [TBL] [Abstract][Full Text] [Related]  

  • 44. A deep learning framework for financial time series using stacked autoencoders and long-short term memory.
    Bao W; Yue J; Rao Y
    PLoS One; 2017; 12(7):e0180944. PubMed ID: 28708865
    [TBL] [Abstract][Full Text] [Related]  

  • 45. Predicting carbon futures prices based on a new hybrid machine learning: Comparative study of carbon prices in different periods.
    Zhang X; Yang K; Lu Q; Wu J; Yu L; Lin Y
    J Environ Manage; 2023 Nov; 346():118962. PubMed ID: 37714085
    [TBL] [Abstract][Full Text] [Related]  

  • 46. Forecasting China carbon price using an error-corrected secondary decomposition hybrid model integrated fuzzy dispersion entropy and deep learning paradigm.
    Yun P; Zhou Y; Liu C; Wu Y; Pan D
    Environ Sci Pollut Res Int; 2024 Mar; 31(11):16530-16553. PubMed ID: 38321281
    [TBL] [Abstract][Full Text] [Related]  

  • 47. A Novel Method for Regional NO
    Liu B; Zhang L; Wang Q; Chen J
    Comput Intell Neurosci; 2021; 2021():6631614. PubMed ID: 33927755
    [TBL] [Abstract][Full Text] [Related]  

  • 48. An innovative coupled model in view of wavelet transform for predicting short-term PM10 concentration.
    Qiao W; Wang Y; Zhang J; Tian W; Tian Y; Yang Q
    J Environ Manage; 2021 Jul; 289():112438. PubMed ID: 33872873
    [TBL] [Abstract][Full Text] [Related]  

  • 49. A Long Short-Term Memory Network Stock Price Prediction with Leading Indicators.
    Wu JM; Sun L; Srivastava G; Lin JC
    Big Data; 2021 Oct; 9(5):343-357. PubMed ID: 34287015
    [TBL] [Abstract][Full Text] [Related]  

  • 50. A novel hybrid approach to forecast crude oil futures using intraday data.
    Manickavasagam J; Visalakshmi S; Apergis N
    Technol Forecast Soc Change; 2020 Sep; 158():120126. PubMed ID: 32518424
    [TBL] [Abstract][Full Text] [Related]  

  • 51. Dynamic Learning Framework for Smooth-Aided Machine-Learning-Based Backbone Traffic Forecasts.
    Hassan MK; Syed Ariffin SH; Ghazali NE; Hamad M; Hamdan M; Hamdi M; Hamam H; Khan S
    Sensors (Basel); 2022 May; 22(9):. PubMed ID: 35591282
    [TBL] [Abstract][Full Text] [Related]  

  • 52. Crude oil price forecasting based on hybridizing wavelet multiple linear regression model, particle swarm optimization techniques, and principal component analysis.
    Shabri A; Samsudin R
    ScientificWorldJournal; 2014; 2014():854520. PubMed ID: 24895666
    [TBL] [Abstract][Full Text] [Related]  

  • 53. An explainable multiscale LSTM model with wavelet transform and layer-wise relevance propagation for daily streamflow forecasting.
    Tao L; Cui Z; He Y; Yang D
    Sci Total Environ; 2024 Jun; 929():172465. PubMed ID: 38615782
    [TBL] [Abstract][Full Text] [Related]  

  • 54. A comparative study of data-driven models for runoff, sediment, and nitrate forecasting.
    Zamani MG; Nikoo MR; Rastad D; Nematollahi B
    J Environ Manage; 2023 Sep; 341():118006. PubMed ID: 37163836
    [TBL] [Abstract][Full Text] [Related]  

  • 55. A novel optimal-hybrid model for daily air quality index prediction considering air pollutant factors.
    Wu Q; Lin H
    Sci Total Environ; 2019 Sep; 683():808-821. PubMed ID: 31154159
    [TBL] [Abstract][Full Text] [Related]  

  • 56. Deep learning models for forecasting and analyzing the implications of COVID-19 spread on some commodities markets volatilities.
    Sadefo Kamdem J; Bandolo Essomba R; Njong Berinyuy J
    Chaos Solitons Fractals; 2020 Nov; 140():110215. PubMed ID: 32839644
    [TBL] [Abstract][Full Text] [Related]  

  • 57. Transductive LSTM for time-series prediction: An application to weather forecasting.
    Karevan Z; Suykens JAK
    Neural Netw; 2020 May; 125():1-9. PubMed ID: 32062409
    [TBL] [Abstract][Full Text] [Related]  

  • 58. LSTM and GRU Neural Networks as Models of Dynamical Processes Used in Predictive Control: A Comparison of Models Developed for Two Chemical Reactors.
    Zarzycki K; Ławryńczuk M
    Sensors (Basel); 2021 Aug; 21(16):. PubMed ID: 34451065
    [TBL] [Abstract][Full Text] [Related]  

  • 59. A CNN-LSTM based deep learning model with high accuracy and robustness for carbon price forecasting: A case of Shenzhen's carbon market in China.
    Shi H; Wei A; Xu X; Zhu Y; Hu H; Tang S
    J Environ Manage; 2024 Feb; 352():120131. PubMed ID: 38266520
    [TBL] [Abstract][Full Text] [Related]  

  • 60. A Hybrid Model for Coronavirus Disease 2019 Forecasting Based on Ensemble Empirical Mode Decomposition and Deep Learning.
    Liu S; Wan Y; Yang W; Tan A; Jian J; Lei X
    Int J Environ Res Public Health; 2022 Dec; 20(1):. PubMed ID: 36612939
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 24.