بدائل البحث:
greatest decrease » treatment decreased (توسيع البحث), greater increase (توسيع البحث)
nn decrease » _ decrease (توسيع البحث), gy decreased (توسيع البحث), b1 decreased (توسيع البحث)
a decrease » _ decrease (توسيع البحث), _ decreased (توسيع البحث), _ decreases (توسيع البحث)
greatest decrease » treatment decreased (توسيع البحث), greater increase (توسيع البحث)
nn decrease » _ decrease (توسيع البحث), gy decreased (توسيع البحث), b1 decreased (توسيع البحث)
a decrease » _ decrease (توسيع البحث), _ decreased (توسيع البحث), _ decreases (توسيع البحث)
-
2401
-
2402
-
2403
-
2404
A Comparison of Pediatric Prehospital Opioid Encounters and Social Vulnerability
منشور في 2024"…The analysis demonstrated that as socioeconomic status (SES) improves, the likelihood of opioid-related activations increases significantly supported by a significant negative linear trend (Estimate = −0.2971, SE = 0.1172, z = −2.54, <i>p</i> = 0.0112. …"
-
2405
-
2406
-
2407
-
2408
-
2409
-
2410
Structure diagram of ensemble model.
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. …"
-
2411
Fitting formula parameter table.
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. …"
-
2412
Test plan.
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. …"
-
2413
Fitting surface parameters.
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. …"
-
2414
Model generalisation validation error analysis.
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. …"
-
2415
Empirical model prediction error analysis.
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. …"
-
2416
Fitting curve parameters.
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. …"
-
2417
Test instrument.
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. …"
-
2418
Empirical model establishment process.
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. …"
-
2419
Model prediction error trend chart.
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. …"
-
2420
Basic physical parameters of red clay.
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. …"