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Journal Abstract Search

522 related items for PubMed ID: 30708163

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  • 2. Long short-term memory - Fully connected (LSTM-FC) neural network for PM2.5 concentration prediction.
    Zhao J, Deng F, Cai Y, Chen J.
    Chemosphere; 2019 Apr; 220():486-492. PubMed ID: 30594800
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  • 3. Long short-term memory neural network for air pollutant concentration predictions: Method development and evaluation.
    Li X, Peng L, Yao X, Cui S, Hu Y, You C, Chi T.
    Environ Pollut; 2017 Dec; 231(Pt 1):997-1004. PubMed ID: 28898956
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  • 5. PM2.5 Prediction with a Novel Multi-Step-Ahead Forecasting Model Based on Dynamic Wind Field Distance.
    Yang M, Fan H, Zhao K.
    Int J Environ Res Public Health; 2019 Nov 14; 16(22):. PubMed ID: 31739449
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  • 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 14; 28(45):64818-64829. PubMed ID: 34318419
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  • 9. PM2.5 forecasting for an urban area based on deep learning and decomposition method.
    Zaini N, Ean LW, Ahmed AN, Abdul Malek M, Chow MF.
    Sci Rep; 2022 Oct 20; 12(1):17565. PubMed ID: 36266317
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  • 11. Ensemble streamflow forecasting based on variational mode decomposition and long short term memory.
    Sun X, Zhang H, Wang J, Shi C, Hua D, Li J.
    Sci Rep; 2022 Jan 11; 12(1):518. PubMed ID: 35017569
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  • 12. Short-term prediction of PM2.5 concentration by hybrid neural network based on sequence decomposition.
    Wu X, Zhu J, Wen Q.
    PLoS One; 2024 Jan 11; 19(5):e0299603. PubMed ID: 38728371
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  • 13. Development of a stacked ensemble model for forecasting and analyzing daily average PM2.5 concentrations in Beijing, China.
    Zhai B, Chen J.
    Sci Total Environ; 2018 Sep 01; 635():644-658. PubMed ID: 29679837
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  • 14. Seasonal prediction of daily PM2.5 concentrations with interpretable machine learning: a case study of Beijing, China.
    Wu Y, Lin S, Shi K, Ye Z, Fang Y.
    Environ Sci Pollut Res Int; 2022 Jun 01; 29(30):45821-45836. PubMed ID: 35150424
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  • 16. 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 29; 20(1):. PubMed ID: 36612939
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  • 17. A hybrid model for enhanced forecasting of PM2.5 spatiotemporal concentrations with high resolution and accuracy.
    Feng X, Zhang X, Henne S, Zhao YB, Liu J, Chen TL, Wang J.
    Environ Pollut; 2024 Aug 15; 355():124263. PubMed ID: 38815889
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