يعرض 1,501 - 1,520 نتائج من 3,940 نتيجة بحث عن 'significant ((((gap decrease) OR (((teer decrease) OR (greatest decrease))))) OR (mean decrease))', وقت الاستعلام: 0.66s تنقيح النتائج
  1. 1501

    Fitting surface parameters. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"
  2. 1502

    Model generalisation validation error analysis. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"
  3. 1503

    Empirical model prediction error analysis. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"
  4. 1504

    Fitting curve parameters. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"
  5. 1505

    Test instrument. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"
  6. 1506

    Empirical model establishment process. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"
  7. 1507

    Model prediction error trend chart. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"
  8. 1508

    Basic physical parameters of red clay. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"
  9. 1509

    BP neural network structure diagram. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"
  10. 1510

    Structure diagram of GBDT model. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"
  11. 1511

    Model prediction error analysis index. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"
  12. 1512

    Fitting curve parameter table. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"
  13. 1513

    Model prediction error analysis. حسب Hongqi Wang (2208238)

    منشور في 2024
    "…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. …"
  14. 1514
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  16. 1516
  17. 1517
  18. 1518
  19. 1519

    Supplementary file 1_Identifying early blood glucose trajectories in sepsis linked to distinct long-term outcomes: a K-means clustering study with external validation.docx حسب Huan Ma (713125)

    منشور في 2025
    "…Conversely, patients with a “high-stable” trajectory (HR: 1.61, 95% CI: 1.35-1.92, P < 0.001) and those exhibiting unstable trends had significantly higher mortality risks (“high-decreasing”, HR: 1.38, 95% CI: 1.16-1.65, P < 0.001; “moderate-increasing”, HR: 1.37, 95% CI: 1.18-1.60, P < 0.001). …"
  20. 1520