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Showing 1 - 20 results of 317 for search '(( binary edge process optimization algorithm ) OR ( primary data models optimization algorithm ))', query time: 0.60s Refine Results
  1. 1
    Proposed Algorithm.

    Proposed Algorithm. by Hend Bayoumi (22693738)

    Published 2025
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  2. 2
    Comparisons between ADAM and NADAM optimizers.

    Comparisons between ADAM and NADAM optimizers. by Hend Bayoumi (22693738)

    Published 2025
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  3. 3
    The parameter settings of the RF algorithm after parameter optimization.

    The parameter settings of the RF algorithm after parameter optimization. by Xini Fang (20861990)

    Published 2025
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  4. 4
    Parameter optimization results of the RF model improved by FCM clustering.

    Parameter optimization results of the RF model improved by FCM clustering. by Xini Fang (20861990)

    Published 2025
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  5. 5
    Comparisons of computation rate performance for different offloading algorithms.for N = 10, 20, 30.

    Comparisons of computation rate performance for different offloading algorithms.for N = 10, 20, 30. by Hend Bayoumi (22693738)

    Published 2025
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  6. 6
    Comparison of total time consumed for different offloading algorithms.for N = 10, 20, 30.

    Comparison of total time consumed for different offloading algorithms.for N = 10, 20, 30. by Hend Bayoumi (22693738)

    Published 2025
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  7. 7
    Evaluation metrics of the models’ performance.

    Evaluation metrics of the models’ performance. by Guangwei Liu (181992)

    Published 2024
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  8. 8
    Pseudocode of artificial dragonfly algorithm.

    Pseudocode of artificial dragonfly algorithm. by Ghassan Ahmed Ali (17041488)

    Published 2023
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  9. 9
    The Hopfield artificial neural network algorithm.

    The Hopfield artificial neural network algorithm. by Ghassan Ahmed Ali (17041488)

    Published 2023
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  10. 10
    Features selected by optimization algorithms.

    Features selected by optimization algorithms. by Afnan M. Alhassan (18349378)

    Published 2024
    “…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”
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  11. 11
    Zimbabwe model outputs on actual and optimized 2016 spending and impact by intervention.

    Zimbabwe model outputs on actual and optimized 2016 spending and impact by intervention. by Nicole Fraser-Hurt (2636833)

    Published 2021
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  12. 12
    Optimized model prediction performance.

    Optimized model prediction performance. by Guang Tu (22054865)

    Published 2025
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  13. 13
    Training error and accuracy for all HNN models.

    Training error and accuracy for all HNN models. by Ghassan Ahmed Ali (17041488)

    Published 2023
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  14. 14
    An Example of a WPT-MEC Network.

    An Example of a WPT-MEC Network. by Hend Bayoumi (22693738)

    Published 2025
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  15. 15
    Related Work Summary.

    Related Work Summary. by Hend Bayoumi (22693738)

    Published 2025
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  16. 16
    Simulation parameters.

    Simulation parameters. by Hend Bayoumi (22693738)

    Published 2025
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  17. 17
    Training losses for N = 10.

    Training losses for N = 10. by Hend Bayoumi (22693738)

    Published 2025
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  18. 18
    Performance Comparison of State-of-the-Art WPT-MEC Offloading Methods.

    Performance Comparison of State-of-the-Art WPT-MEC Offloading Methods. by Hend Bayoumi (22693738)

    Published 2025
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  19. 19
    The evolution of the Wireless Power Transfer (WPT) time fraction β over simulation frames.

    The evolution of the Wireless Power Transfer (WPT) time fraction β over simulation frames. by Hend Bayoumi (22693738)

    Published 2025
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  20. 20
    Normalized computation rate for N = 10.

    Normalized computation rate for N = 10. by Hend Bayoumi (22693738)

    Published 2025
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