Search alternatives:
learning optimization » learning motivation (Expand Search), lead optimization (Expand Search)
based optimization » whale optimization (Expand Search)
data learning » meta learning (Expand Search), deep learning (Expand Search), a learning (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
binary b » binary _ (Expand Search)
b based » _ based (Expand Search), 1 based (Expand Search), 2 based (Expand Search)
Showing 21 - 40 results of 131 for search '(( binary b based optimization algorithm ) OR ( binary data learning optimization algorithm ))*', query time: 1.12s Refine Results
  1. 21
    Normalized computation rate for N = 10.

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

    Published 2025
    “…EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …”
    Save to List
    Saved in:
  2. 22
    Summary of Notations Used in this paper.

    Summary of Notations Used in this paper. by Hend Bayoumi (22693738)

    Published 2025
    “…EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …”
    Save to List
    Saved in:
  3. 23
    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
    Subjects:
    Save to List
    Saved in:
  4. 24
    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
    Subjects:
    Save to List
    Saved in:
  5. 25
    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
    Subjects:
    Save to List
    Saved in:
  6. 26
    CEC 2019 benchmark characteristics.

    CEC 2019 benchmark characteristics. by Nebojsa Bacanin (13932723)

    Published 2022
    Subjects:
    Save to List
    Saved in:
  7. 27
    Results of Holm’s step-down procedure.

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

    Published 2022
    Subjects:
    Save to List
    Saved in:
  8. 28
    Friedman ranks of tested methods on CEC2019 benchmark functions.

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

    Published 2022
    Subjects:
    Save to List
    Saved in:
  9. 29
    V-shaped transfer functions.

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

    Published 2022
    Subjects:
    Save to List
    Saved in:
  10. 30
    Resilts of Friedman and Iman-Davenport tests (<i>α</i> = 0.05).

    Resilts of Friedman and Iman-Davenport tests (<i>α</i> = 0.05). by Nebojsa Bacanin (13932723)

    Published 2022
    Subjects:
    Save to List
    Saved in:
  11. 31
    Mean fitness and standard deviation results of compared approaches on CEC2019 benchmark functions.

    Mean fitness and standard deviation results of compared approaches on CEC2019 benchmark functions. by Nebojsa Bacanin (13932723)

    Published 2022
    Subjects:
    Save to List
    Saved in:
  12. 32
    Error rate convergence graphs.

    Error rate convergence graphs. by Nebojsa Bacanin (13932723)

    Published 2022
    Subjects:
    Save to List
    Saved in:
  13. 33
    COVID-19 dataset description.

    COVID-19 dataset description. by Nebojsa Bacanin (13932723)

    Published 2022
    Subjects:
    Save to List
    Saved in:
  14. 34
    Control parameter settings for comparative feature selection methods.

    Control parameter settings for comparative feature selection methods. by Nebojsa Bacanin (13932723)

    Published 2022
    Subjects:
    Save to List
    Saved in:
  15. 35
    The result of the Wilcoxon test of presented COFFO against compared methods.

    The result of the Wilcoxon test of presented COFFO against compared methods. by Nebojsa Bacanin (13932723)

    Published 2022
    Subjects:
    Save to List
    Saved in:
  16. 36
    COFFO control parameters.

    COFFO control parameters. by Nebojsa Bacanin (13932723)

    Published 2022
    Subjects:
    Save to List
    Saved in:
  17. 37
    Convergence graphs for ten CEC 2019 benchmark functions and direct comparison between COFFO and FFO.

    Convergence graphs for ten CEC 2019 benchmark functions and direct comparison between COFFO and FFO. by Nebojsa Bacanin (13932723)

    Published 2022
    Subjects:
    Save to List
    Saved in:
  18. 38
    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
    Save to List
    Saved in:
  19. 39
    The data processing and analysis pipeline.

    The data processing and analysis pipeline. by Xin Zhang (35492)

    Published 2025
    Save to List
    Saved in:
  20. 40
    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
    Save to List
    Saved in:

Search Tools: