يعرض 21 - 40 نتائج من 149 نتيجة بحث عن '(( significantly increased decrease ) OR ( significance ((set decrease) OR (mean decrease)) ))~', وقت الاستعلام: 0.57s تنقيح النتائج
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    Structure diagram of ensemble 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. …"
  3. 23

    Fitting formula 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. …"
  4. 24

    Test plan. 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. 25

    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. …"
  6. 26

    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. …"
  7. 27

    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. …"
  8. 28

    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. …"
  9. 29

    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. …"
  10. 30

    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. …"
  11. 31

    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. …"
  12. 32

    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. …"
  13. 33

    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. …"
  14. 34

    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. …"
  15. 35

    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. …"
  16. 36

    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. …"
  17. 37

    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. …"
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