Search alternatives:
bayesian optimization » based optimization (Expand Search)
using optimization » joint optimization (Expand Search), design optimization (Expand Search), step optimization (Expand Search)
aided bayesian » fitted bayesian (Expand Search), naive bayesian (Expand Search), applied bayesian (Expand Search)
binary task » binary mask (Expand Search)
task using » tasks using (Expand Search), risk using (Expand Search)
Showing 1 - 20 results of 101 for search '(( binary aided bayesian optimization algorithm ) OR ( binary task using optimization algorithm ))*', query time: 0.52s Refine Results
  1. 1
    Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things

    Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things by Ashok Kumar K (21441108)

    Published 2025
    “…Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …”
    Save to List
    Saved in:
  2. 2
    Proposed Algorithm.

    Proposed Algorithm. by Hend Bayoumi (22693738)

    Published 2025
    Subjects:
    Save to List
    Saved in:
  3. 3
    CDF of task latency, approximated as the inverse of the achieved computation rate.

    CDF of task latency, approximated as the inverse of the achieved computation rate. by Hend Bayoumi (22693738)

    Published 2025
    Subjects:
    Save to List
    Saved in:
  4. 4
    Comparisons between ADAM and NADAM optimizers.

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

    Published 2025
    Subjects:
    Save to List
    Saved in:
  5. 5
    Summary of Notations Used in this paper.

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

    Published 2025
    Subjects:
    Save to List
    Saved in:
  6. 6
    The workflow diagram for the gene expression biomarker study which involve using principal component analysis (PCA) to reduce the number of features (principal components), thus requiring fewer qubits.

    The workflow diagram for the gene expression biomarker study which involve using principal component analysis (PCA) to reduce the number of features (principal components), thus re... by Aninda Astuti (21736334)

    Published 2025
    Save to List
    Saved in:
  7. 7
    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
    Subjects:
    Save to List
    Saved in:
  8. 8
    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
    Subjects:
    Save to List
    Saved in:
  9. 9
    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. …”
    Save to List
    Saved in:
  10. 10
    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. …”
    Save to List
    Saved in:
  11. 11
    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. …”
    Save to List
    Saved in:
  12. 12
    An Example of a WPT-MEC Network.

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

    Published 2025
    Subjects:
    Save to List
    Saved in:
  13. 13
    Related Work Summary.

    Related Work Summary. by Hend Bayoumi (22693738)

    Published 2025
    Subjects:
    Save to List
    Saved in:
  14. 14
    Simulation parameters.

    Simulation parameters. by Hend Bayoumi (22693738)

    Published 2025
    Subjects:
    Save to List
    Saved in:
  15. 15
    Training losses for N = 10.

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

    Published 2025
    Subjects:
    Save to List
    Saved in:
  16. 16
    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
    Subjects:
    Save to List
    Saved in:
  17. 17
    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
    Subjects:
    Save to List
    Saved in:
  18. 18
    Normalized computation rate for N = 10.

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

    Published 2025
    Subjects:
    Save to List
    Saved in:
  19. 19
    Comparison between Bisection and Newton-Raphson in terms of (A) total time consumed, and (B) maximum computation rate.

    Comparison between Bisection and Newton-Raphson in terms of (A) total time consumed, and (B) maximum computation rate. by Hend Bayoumi (22693738)

    Published 2025
    Subjects:
    Save to List
    Saved in:
  20. 20
    Latent state estimations for simulated data.

    Latent state estimations for simulated data. by Samiul Alam (18563323)

    Published 2024
    Save to List
    Saved in:

Search Tools: