يعرض 641 - 660 نتائج من 1,284 نتيجة بحث عن 'significantly ((((teer decrease) OR (nn decrease))) OR (linear decrease))', وقت الاستعلام: 0.45s تنقيح النتائج
  1. 641

    Ceramic bearings. حسب Longfei Gao (698900)

    منشور في 2025
    "…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …"
  2. 642

    Geometric contact arc length model. حسب Longfei Gao (698900)

    منشور في 2025
    "…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …"
  3. 643

    Indentation fracture mechanics model. حسب Longfei Gao (698900)

    منشور في 2025
    "…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …"
  4. 644

    Grinding particle cutting machining model. حسب Longfei Gao (698900)

    منشور في 2025
    "…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …"
  5. 645

    Three stages of abrasive cutting process. حسب Longfei Gao (698900)

    منشور في 2025
    "…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …"
  6. 646

    CNN-LSTM action recognition process. حسب Longfei Gao (698900)

    منشور في 2025
    "…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …"
  7. 647

    Differences in magnitude and velocity of decay of the different compartments of the viral reservoir. حسب Maria C. Puertas (8801768)

    منشور في 2025
    "…<p>A. The overall decrease in each fraction of the viral reservoir during the first year after ART initiation is expressed as the ratio of week 48 to baseline values. …"
  8. 648
  9. 649
  10. 650
  11. 651

    Mean parameter values for the selected crops. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"
  12. 652

    Performance comparison of ML models. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"
  13. 653

    Comparative data of different soil samples. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"
  14. 654

    Confusion matrix of random forest model. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"
  15. 655

    Sensor value scenario for fuzzy logic algorithm. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"
  16. 656

    Evaluation metrics of selected ML models. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"
  17. 657

    Block diagram of the proposed system. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"
  18. 658

    Chart for applicable amount of fertilizers. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"
  19. 659

    Cost analysis of irrigation controller unit. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"
  20. 660

    Run times of two algorithms. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"