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Showing 901 - 920 results of 1,782 for search 'significantly ((linear decrease) OR (larger decrease))', query time: 0.37s Refine Results
  1. 901
  2. 902
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  4. 904

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

    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. …”
  5. 905

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

    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. …”
  6. 906

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

    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. …”
  7. 907

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

    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. …”
  8. 908

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

    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. …”
  9. 909

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

    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. …”
  10. 910

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

    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. …”
  11. 911

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

    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. …”
  12. 912

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

    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. …”
  13. 913

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

    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. …”
  14. 914
  15. 915

    Flow chart of Fuzzy Logic based control system. by Gourab Saha (8987405)

    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. …”
  16. 916

    Block diagram for IoT-based irrigation system. by Gourab Saha (8987405)

    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. …”
  17. 917

    Flow chart of Average Value-based control system. by Gourab Saha (8987405)

    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. …”
  18. 918

    Hardware design for IoT-based irrigation system. by Gourab Saha (8987405)

    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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    Characteristics of the study subjects (N = 39). by Layane S. P. Costa (22530327)

    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). …”