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Showing 1 - 20 results of 92 for search '(( binary model lead optimization algorithm ) OR ( binary time policy optimization algorithm ))*', query time: 0.61s Refine Results
  1. 1
    Sensitivity values of IRBMO vs. other binary algorithms.

    Sensitivity values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

    Published 2025
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  2. 2
    Specificity values of IRBMO vs. other binary algorithms.

    Specificity values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

    Published 2025
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  3. 3
    Fitness values of IRBMO vs. other binary algorithms.

    Fitness values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

    Published 2025
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  4. 4
    Number of features selected for IRBMO vs. other binary algorithms.

    Number of features selected for IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

    Published 2025
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  5. 5
    Classification accuracy values of IRBMO vs. other binary algorithms.

    Classification accuracy values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

    Published 2025
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  6. 6
    F-score values of IRBMO vs. other binary algorithms.

    F-score values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

    Published 2025
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  7. 7
    CSTP-MAC algorithm backoff time-slots vs IEEE 802.15.4 binary backoff exponential algorithm backoff time-slots.

    CSTP-MAC algorithm backoff time-slots vs IEEE 802.15.4 binary backoff exponential algorithm backoff time-slots. by Innocent Uzougbo Onwuegbuzie (9243166)

    Published 2020
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  8. 8
    The confidence curve of a binary image.

    The confidence curve of a binary image. by Dingming Yang (8505990)

    Published 2022
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  9. 9
    The confidence change of the binary image after iteration.

    The confidence change of the binary image after iteration. by Dingming Yang (8505990)

    Published 2022
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  10. 10
    Algorithm for optimal decision determination in sequential decision-making.

    Algorithm for optimal decision determination in sequential decision-making. by Mariko I. Ito (5007323)

    Published 2023
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  11. 11
    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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  12. 12
    Proposed Algorithm.

    Proposed Algorithm. by Hend Bayoumi (22693738)

    Published 2025
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  13. 13
    Algorithm for generating hyperparameter.

    Algorithm for generating hyperparameter. by Balraj Preet Kaur (20370832)

    Published 2024
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  14. 14
    Comparisons between ADAM and NADAM optimizers.

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

    Published 2025
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  15. 15
    The Pseudo-Code of the IRBMO Algorithm.

    The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

    Published 2025
    “…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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  16. 16
    Results of machine learning algorithm.

    Results of machine learning algorithm. by Balraj Preet Kaur (20370832)

    Published 2024
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  17. 17
    ROC comparison of machine learning algorithm.

    ROC comparison of machine learning algorithm. by Balraj Preet Kaur (20370832)

    Published 2024
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  18. 18
    Optimization of tracking parameters based on <i>P</i><sub><i>swap</i></sub>.

    Optimization of tracking parameters based on <i>P</i><sub><i>swap</i></sub>. by Benjamin Gallois (10131683)

    Published 2021
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  19. 19
    IRBMO vs. meta-heuristic algorithms boxplot.

    IRBMO vs. meta-heuristic algorithms boxplot. by Chenyi Zhu (9383370)

    Published 2025
    “…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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  20. 20
    IRBMO vs. feature selection algorithm boxplot.

    IRBMO vs. feature selection algorithm boxplot. by Chenyi Zhu (9383370)

    Published 2025
    “…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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