بدائل البحث:
linear decrease » linear increase (توسيع البحث)
teer decrease » mean decrease (توسيع البحث), greater decrease (توسيع البحث)
nn decrease » _ decrease (توسيع البحث), a decrease (توسيع البحث), mean decrease (توسيع البحث)
linear decrease » linear increase (توسيع البحث)
teer decrease » mean decrease (توسيع البحث), greater decrease (توسيع البحث)
nn decrease » _ decrease (توسيع البحث), a decrease (توسيع البحث), mean decrease (توسيع البحث)
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641
Ceramic bearings.
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. …"
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642
Geometric contact arc length model.
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. …"
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643
Indentation fracture mechanics model.
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. …"
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644
Grinding particle cutting machining model.
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. …"
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645
Three stages of abrasive cutting process.
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. …"
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646
CNN-LSTM action recognition process.
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. …"
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647
Differences in magnitude and velocity of decay of the different compartments of the viral reservoir.
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. …"
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648
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649
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650
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651
Mean parameter values for the selected crops.
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. …"
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652
Performance comparison of ML models.
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. …"
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653
Comparative data of different soil samples.
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. …"
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654
Confusion matrix of random forest model.
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. …"
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655
Sensor value scenario for fuzzy logic algorithm.
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. …"
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656
Evaluation metrics of selected ML models.
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. …"
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657
Block diagram of the proposed system.
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. …"
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658
Chart for applicable amount of fertilizers.
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. …"
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659
Cost analysis of irrigation controller unit.
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. …"
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660
Run times of two algorithms.
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. …"