Search alternatives:
larger decrease » marked decrease (Expand Search)
linear decrease » linear increase (Expand Search)
nn decrease » _ decrease (Expand Search), a decrease (Expand Search), mean decrease (Expand Search)
larger decrease » marked decrease (Expand Search)
linear decrease » linear increase (Expand Search)
nn decrease » _ decrease (Expand Search), a decrease (Expand Search), mean decrease (Expand Search)
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921
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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922
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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923
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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924
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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925
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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926
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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927
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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928
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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929
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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930
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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931
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932
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. …”
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933
Block diagram for IoT-based irrigation 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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934
Flow chart of Average Value-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. …”
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935
Hardware design for IoT-based irrigation 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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936
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937
Characteristics of the study subjects (N = 39).
Published 2025“…EELV increased in PL (+ 0.7 mL/kg PBW), PR (+2.0), and AR (+2.8), but decreased in AL (−2.3) (<i><i>p</i></i> < 0.001). In the bilateral protocol (n = 10, 70% male; 23.6 ± 3.2 years), regional ventilation showed no significant effects of position, ROI, or interaction (<i><i>p</i></i> > 0.05). …”
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938
Flowchart of study.
Published 2025“…EELV increased in PL (+ 0.7 mL/kg PBW), PR (+2.0), and AR (+2.8), but decreased in AL (−2.3) (<i><i>p</i></i> < 0.001). In the bilateral protocol (n = 10, 70% male; 23.6 ± 3.2 years), regional ventilation showed no significant effects of position, ROI, or interaction (<i><i>p</i></i> > 0.05). …”
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939
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940