Showing 2,281 - 2,300 results of 18,396 for search 'significant ((((((shape decrease) OR (mean decrease))) OR (a decrease))) OR (small decrease))', query time: 0.51s Refine Results
  1. 2281

    Fitting formula parameter table. by Hongqi Wang (2208238)

    Published 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. 2282

    Test plan. by Hongqi Wang (2208238)

    Published 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. 2283

    Fitting surface parameters. by Hongqi Wang (2208238)

    Published 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. 2284

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

    Published 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. 2285

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

    Published 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. 2286

    Fitting curve parameters. by Hongqi Wang (2208238)

    Published 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. 2287

    Test instrument. by Hongqi Wang (2208238)

    Published 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. 2288

    Empirical model establishment process. by Hongqi Wang (2208238)

    Published 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. 2289

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

    Published 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. 2290

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

    Published 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. 2291

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

    Published 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. 2292

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

    Published 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. 2293

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

    Published 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. 2294

    Fitting curve parameter table. by Hongqi Wang (2208238)

    Published 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. 2295

    Model prediction error analysis. by Hongqi Wang (2208238)

    Published 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. 2296

    Supplementary file 1_Forced intensity-controlled endurance training on a small-animal treadmill machine inducing murine cardiac hypertrophy: insights and comparison to voluntary ru... by Maximillian Fischer (14758063)

    Published 2025
    “…Wild-type male C57BL/6 mice at 8 weeks old were subjected to forced endurance training using a small-animal treadmill or sedentary age-matched control. …”
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  20. 2300

    Data information. by Yuxin Wei (11510974)

    Published 2025
    “…<div><p>Global warming is exacerbating the occurrence of droughts, which have a significant impact on society. Drought is one of the main factors limiting the development of the Santun River Irrigation Area in Xinjiang. …”