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allocation algorithm » location algorithm (Expand Search), selection algorithm (Expand Search), detection algorithm (Expand Search)
process optimization » model optimization (Expand Search)
time resource » situ resource (Expand Search), firm resource (Expand Search), optimize resource (Expand Search)
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Showing 1 - 20 results of 100 for search '(( binary time resource allocation algorithm ) OR ( binary data process optimization algorithm ))*', query time: 0.44s Refine Results
  1. 1
    Dynamic resource allocation process.

    Dynamic resource allocation process. by Yixian Wen (12201388)

    Published 2025
    “…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
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  2. 2
    Event-driven data flow processing.

    Event-driven data flow processing. by Yixian Wen (12201388)

    Published 2025
    “…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
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  3. 3
    The flowchart showing the optimization process of the hybrid methods using BEOSA as the base algorithm and SA and FFA as integrated algorithms.

    The flowchart showing the optimization process of the hybrid methods using BEOSA as the base algorithm and SA and FFA as integrated algorithms. by Olaide N. Oyelade (14047002)

    Published 2023
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  4. 4
    The result of the accuracy of tested algorithms.

    The result of the accuracy of tested algorithms. by Nebojsa Bacanin (13932723)

    Published 2022
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  5. 5
    Feature selection ratio results for tested algorithms.

    Feature selection ratio results for tested algorithms. by Nebojsa Bacanin (13932723)

    Published 2022
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  6. 6
    Best fitness value results for tested algorithms.

    Best fitness value results for tested algorithms. by Nebojsa Bacanin (13932723)

    Published 2022
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  7. 7
    Mean fitness value results for tested algorithms.

    Mean fitness value results for tested algorithms. by Nebojsa Bacanin (13932723)

    Published 2022
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  8. 8
    Standard deviation of fitness value results for tested algorithms.

    Standard deviation of fitness value results for tested algorithms. by Nebojsa Bacanin (13932723)

    Published 2022
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  9. 9
    a) Accuracy and b) selected feature size of algorithms on the COVID-19 dataset.

    a) Accuracy and b) selected feature size of algorithms on the COVID-19 dataset. by Nebojsa Bacanin (13932723)

    Published 2022
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  10. 10
    Optimizing Kernel Transformations to Handle Binary Class Imbalanced Dataset Classification

    Optimizing Kernel Transformations to Handle Binary Class Imbalanced Dataset Classification by Vaibhavi Patel (19843282)

    Published 2024
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  11. 11
    Boxplots analysis of the tested algorithms using average error rate across 21 datasets.

    Boxplots analysis of the tested algorithms using average error rate across 21 datasets. by Nebojsa Bacanin (13932723)

    Published 2022
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  12. 12
    S1 Dataset - Novel chaotic oppositional fruit fly optimization algorithm for feature selection applied on COVID 19 patients’ health prediction

    S1 Dataset - Novel chaotic oppositional fruit fly optimization algorithm for feature selection applied on COVID 19 patients’ health prediction by Nebojsa Bacanin (13932723)

    Published 2022
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  13. 13
    The result of the best fitness value, mean fitness value, standard deviation of fitness value and feature selection ratio of algorithms on the COVID-19 dataset.

    The result of the best fitness value, mean fitness value, standard deviation of fitness value and feature selection ratio of algorithms on the COVID-19 dataset. by Nebojsa Bacanin (13932723)

    Published 2022
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  14. 14
    An optimization process of the proposed hybrid BEOSA (HBEOSA) combining both SA and FFA methods into BEOSA.

    An optimization process of the proposed hybrid BEOSA (HBEOSA) combining both SA and FFA methods into BEOSA. by Olaide N. Oyelade (14047002)

    Published 2023
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  15. 15
    Confusion matrix.

    Confusion matrix. by Yixian Wen (12201388)

    Published 2025
    “…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
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  16. 16
    Parameter settings.

    Parameter settings. by Yixian Wen (12201388)

    Published 2025
    “…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
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  17. 17
    CEC 2019 benchmark characteristics.

    CEC 2019 benchmark characteristics. by Nebojsa Bacanin (13932723)

    Published 2022
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  18. 18
    Results of Holm’s step-down procedure.

    Results of Holm’s step-down procedure. by Nebojsa Bacanin (13932723)

    Published 2022
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  19. 19
    Friedman ranks of tested methods on CEC2019 benchmark functions.

    Friedman ranks of tested methods on CEC2019 benchmark functions. by Nebojsa Bacanin (13932723)

    Published 2022
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  20. 20
    V-shaped transfer functions.

    V-shaped transfer functions. by Nebojsa Bacanin (13932723)

    Published 2022
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