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Showing 21 - 40 results of 262 for search '(( binary basis function optimization algorithm ) OR ( binary used model optimization algorithm ))', query time: 0.54s Refine Results
  1. 21
    The AD-PSO-Guided WOA LSTM algorithm RMSE is based on the objective function compared to different algorithms.

    The AD-PSO-Guided WOA LSTM algorithm RMSE is based on the objective function compared to different algorithms. by Ahmed M. Elshewey (21463867)

    Published 2025
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  2. 22
    Total computational cost of the proposed AD-PSO-Guided WOA-LSTM algorithm compared with another algorithm.

    Total computational cost of the proposed AD-PSO-Guided WOA-LSTM algorithm compared with another algorithm. by Ahmed M. Elshewey (21463867)

    Published 2025
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  3. 23
    Adaptive dynamic algorithm for Australia rainfall.

    Adaptive dynamic algorithm for Australia rainfall. by Ahmed M. Elshewey (21463867)

    Published 2025
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  4. 24
    Hyperparameters of the LSTM Model.

    Hyperparameters of the LSTM Model. by Ahmed M. Elshewey (21463867)

    Published 2025
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  5. 25
    Prediction results of individual models.

    Prediction results of individual models. by Ahmed M. Elshewey (21463867)

    Published 2025
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  6. 26
    Fig 3 -

    Fig 3 - by Ali Ahmed (2567584)

    Published 2020
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  7. 27
    Metrics for evaluating the performance of the proposed model.

    Metrics for evaluating the performance of the proposed model. by Ahmed M. Elshewey (21463867)

    Published 2025
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  8. 28
    RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values .

    RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values . by Jakub Stoklosa (3315042)

    Published 2023
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  9. 29
    Best optimizer results of Lightbgm.

    Best optimizer results of Lightbgm. by Balraj Preet Kaur (20370832)

    Published 2024
    “…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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  10. 30
    Best optimizer results of Adaboost.

    Best optimizer results of Adaboost. by Balraj Preet Kaur (20370832)

    Published 2024
    “…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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  11. 31
    Best optimizer results of Lightbgm.

    Best optimizer results of Lightbgm. by Balraj Preet Kaur (20370832)

    Published 2024
    “…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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  12. 32
    Random forest with hyperparameter optimization.

    Random forest with hyperparameter optimization. by Balraj Preet Kaur (20370832)

    Published 2024
    “…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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  13. 33
    Best optimizer results of KNN.

    Best optimizer results of KNN. by Balraj Preet Kaur (20370832)

    Published 2024
    “…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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  14. 34
    Best optimizer results of KNN.

    Best optimizer results of KNN. by Balraj Preet Kaur (20370832)

    Published 2024
    “…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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  15. 35
    Ensemble model architecture.

    Ensemble model architecture. by Balraj Preet Kaur (20370832)

    Published 2024
    “…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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  16. 36
    Comparison between LSTM, LSTM-BOA, LSTM-CBOA and ILSTM using KDDTest+ and KDDTest-21 in binary classification with average 10 runs.

    Comparison between LSTM, LSTM-BOA, LSTM-CBOA and ILSTM using KDDTest+ and KDDTest-21 in binary classification with average 10 runs. by Asmaa Ahmed Awad (16726315)

    Published 2023
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  17. 37
    Flow diagram of the proposed model.

    Flow diagram of the proposed model. by Uğur Ejder (22683228)

    Published 2025
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  18. 38
    Comparison table of the proposed model.

    Comparison table of the proposed model. by Balraj Preet Kaur (20370832)

    Published 2024
    “…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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  19. 39
    Confusion matrix of ensemble model.

    Confusion matrix of ensemble model. by Balraj Preet Kaur (20370832)

    Published 2024
    “…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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  20. 40
    Best optimizer results of Decision tree.

    Best optimizer results of Decision tree. by Balraj Preet Kaur (20370832)

    Published 2024
    “…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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