Search alternatives:
significant linear » significant clinical (Expand Search), significant gender (Expand Search), significant level (Expand Search)
greatest decrease » treatment decreased (Expand Search), greater increase (Expand Search)
better decrease » greater decrease (Expand Search), teer decrease (Expand Search), between decreased (Expand Search)
linear decrease » linear increase (Expand Search)
significant linear » significant clinical (Expand Search), significant gender (Expand Search), significant level (Expand Search)
greatest decrease » treatment decreased (Expand Search), greater increase (Expand Search)
better decrease » greater decrease (Expand Search), teer decrease (Expand Search), between decreased (Expand Search)
linear decrease » linear increase (Expand Search)
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1141
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1142
Grid independence test.
Published 2025“…The results indicate that schemes 1, 2, and 4 all have significant low-speed vortices in the return water zone (D zone). …”
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1143
Physical picture of flow channel of emitter.
Published 2025“…The results indicate that schemes 1, 2, and 4 all have significant low-speed vortices in the return water zone (D zone). …”
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1144
The test results of relative flow of emitters.
Published 2025“…The results indicate that schemes 1, 2, and 4 all have significant low-speed vortices in the return water zone (D zone). …”
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1145
The details of flow chart.
Published 2025“…The results indicate that schemes 1, 2, and 4 all have significant low-speed vortices in the return water zone (D zone). …”
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1146
The physical short-period clogging test device.
Published 2025“…The results indicate that schemes 1, 2, and 4 all have significant low-speed vortices in the return water zone (D zone). …”
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1147
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1148
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1149
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1150
Mean parameter values for the selected crops.
Published 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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1151
Performance comparison of ML models.
Published 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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1152
Comparative data of different soil samples.
Published 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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1153
Confusion matrix of random forest model.
Published 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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1154
Sensor value scenario for fuzzy logic algorithm.
Published 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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1155
Evaluation metrics of selected ML models.
Published 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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1156
Block diagram of the proposed system.
Published 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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1157
Chart for applicable amount of fertilizers.
Published 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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1158
Cost analysis of irrigation controller unit.
Published 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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1159
Run times of two algorithms.
Published 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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1160
Flow chart of Fuzzy Logic based control system.
Published 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. …”