Showing 2,301 - 2,320 results of 4,658 for search 'significantly ((((((lower decrease) OR (teer decrease))) OR (nn decrease))) OR (linear decrease))', query time: 0.45s Refine Results
  1. 2301

    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. …”
  2. 2302

    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. …”
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  4. 2304

    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. …”
  5. 2305

    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. …”
  6. 2306

    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. …”
  7. 2307

    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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  10. 2310

    Example of sample data. by Xiying Wang (4859998)

    Published 2025
    “…In contrast, the EGA-BPNN model achieves a significantly lower mean absolute relative error of 0.41% for single-flow prediction, demonstrating superior prediction performance. …”
  11. 2311

    Structure of BPNN. by Xiying Wang (4859998)

    Published 2025
    “…In contrast, the EGA-BPNN model achieves a significantly lower mean absolute relative error of 0.41% for single-flow prediction, demonstrating superior prediction performance. …”
  12. 2312

    The workflow of EGA-BPNN. by Xiying Wang (4859998)

    Published 2025
    “…In contrast, the EGA-BPNN model achieves a significantly lower mean absolute relative error of 0.41% for single-flow prediction, demonstrating superior prediction performance. …”
  13. 2313

    S1 Data - by Xiying Wang (4859998)

    Published 2025
    “…In contrast, the EGA-BPNN model achieves a significantly lower mean absolute relative error of 0.41% for single-flow prediction, demonstrating superior prediction performance. …”
  14. 2314

    Algorithm flow of the GA-BPNN model. by Xiying Wang (4859998)

    Published 2025
    “…In contrast, the EGA-BPNN model achieves a significantly lower mean absolute relative error of 0.41% for single-flow prediction, demonstrating superior prediction performance. …”
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