Showing 1,141 - 1,160 results of 2,465 for search '(( significantly ((better decrease) OR (greatest decrease)) ) OR ( significant linear decrease ))', query time: 0.43s Refine Results
  1. 1141
  2. 1142

    Grid independence test. by Zhen Zhao (159931)

    Published 2025
    “…The results indicate that schemes 1, 2, and 4 all have significant low-speed vortices in the return water zone (D zone). …”
  3. 1143

    Physical picture of flow channel of emitter. by Zhen Zhao (159931)

    Published 2025
    “…The results indicate that schemes 1, 2, and 4 all have significant low-speed vortices in the return water zone (D zone). …”
  4. 1144

    The test results of relative flow of emitters. by Zhen Zhao (159931)

    Published 2025
    “…The results indicate that schemes 1, 2, and 4 all have significant low-speed vortices in the return water zone (D zone). …”
  5. 1145

    The details of flow chart. by Zhen Zhao (159931)

    Published 2025
    “…The results indicate that schemes 1, 2, and 4 all have significant low-speed vortices in the return water zone (D zone). …”
  6. 1146

    The physical short-period clogging test device. by Zhen Zhao (159931)

    Published 2025
    “…The results indicate that schemes 1, 2, and 4 all have significant low-speed vortices in the return water zone (D zone). …”
  7. 1147
  8. 1148
  9. 1149
  10. 1150

    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. …”
  11. 1151

    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. …”
  12. 1152

    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. …”
  13. 1153

    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. …”
  14. 1154

    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. …”
  15. 1155

    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. …”
  16. 1156

    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. …”
  17. 1157

    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. …”
  18. 1158

    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. …”
  19. 1159

    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. …”
  20. 1160

    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. …”