يعرض 1,901 - 1,920 نتائج من 10,117 نتيجة بحث عن 'significantly ((((we decrease) OR (((greater decrease) OR (mean decrease))))) OR (linear decrease))', وقت الاستعلام: 0.35s تنقيح النتائج
  1. 1901

    Amplitude for A/L = 0.02. حسب Muhammad Hammad Bucha (21736111)

    منشور في 2025
    "…Increased surface roughness significantly reduced power output, flapping frequency, and amplitude. …"
  2. 1902

    Graph for maximum Frequency at G<sub>y</sub> = 0. حسب Muhammad Hammad Bucha (21736111)

    منشور في 2025
    "…Increased surface roughness significantly reduced power output, flapping frequency, and amplitude. …"
  3. 1903

    Graph for maximum Power at G<sub>y</sub> = 0. حسب Muhammad Hammad Bucha (21736111)

    منشور في 2025
    "…Increased surface roughness significantly reduced power output, flapping frequency, and amplitude. …"
  4. 1904

    Amplitude for A/L = 0.03. حسب Muhammad Hammad Bucha (21736111)

    منشور في 2025
    "…Increased surface roughness significantly reduced power output, flapping frequency, and amplitude. …"
  5. 1905

    Summary of experimentation results. حسب Muhammad Hammad Bucha (21736111)

    منشور في 2025
    "…Increased surface roughness significantly reduced power output, flapping frequency, and amplitude. …"
  6. 1906

    Piezoelectric eel. حسب Muhammad Hammad Bucha (21736111)

    منشور في 2025
    "…Increased surface roughness significantly reduced power output, flapping frequency, and amplitude. …"
  7. 1907
  8. 1908
  9. 1909
  10. 1910
  11. 1911

    <b>Data for s</b><b>easonal variations in coral lipids and their significance for energy maintenance in the </b><b>South China Sea</b> حسب Hongyan Mo (19721569)

    منشور في 2024
    "…<p dir="ltr">In recent years, the intensification of global warming and extreme climate have led to an increase in the frequency and severity of coral bleaching. Coral bleaching means a decrease in symbiotic zooxanthellae density (ZD). …"
  12. 1912
  13. 1913
  14. 1914

    Major hyperparameters of RF-SVR. حسب Jintao Li (448681)

    منشور في 2024
    "…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R<sup>2</sup> value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …"
  15. 1915

    Pseudo code for coupling model execution process. حسب Jintao Li (448681)

    منشور في 2024
    "…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R<sup>2</sup> value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …"
  16. 1916

    Major hyperparameters of RF-MLPR. حسب Jintao Li (448681)

    منشور في 2024
    "…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R<sup>2</sup> value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …"
  17. 1917

    Results of RF algorithm screening factors. حسب Jintao Li (448681)

    منشور في 2024
    "…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R<sup>2</sup> value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …"
  18. 1918

    Schematic diagram of the basic principles of SVR. حسب Jintao Li (448681)

    منشور في 2024
    "…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R<sup>2</sup> value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …"
  19. 1919
  20. 1920