Search alternatives:
fasting optimization » routing optimization (Expand Search), learning optimization (Expand Search), drawing optimization (Expand Search)
process optimization » model optimization (Expand Search)
data process » data processing (Expand Search), damage process (Expand Search), data access (Expand Search)
binary high » dietary high (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
Showing 21 - 40 results of 102 for search '(( binary high fasting optimization algorithm ) OR ( binary data process optimization algorithm ))', query time: 0.74s Refine Results
  1. 21
    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
    Subjects:
    Save to List
    Saved in:
  2. 22
    CEC 2019 benchmark characteristics.

    CEC 2019 benchmark characteristics. by Nebojsa Bacanin (13932723)

    Published 2022
    Subjects:
    Save to List
    Saved in:
  3. 23
    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:
  4. 24
    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:
  5. 25
    V-shaped transfer functions.

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

    Published 2022
    Subjects:
    Save to List
    Saved in:
  6. 26
    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:
  7. 27
    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:
  8. 28
    Error rate convergence graphs.

    Error rate convergence graphs. by Nebojsa Bacanin (13932723)

    Published 2022
    Subjects:
    Save to List
    Saved in:
  9. 29
    COVID-19 dataset description.

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

    Published 2022
    Subjects:
    Save to List
    Saved in:
  10. 30
    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:
  11. 31
    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:
  12. 32
    COFFO control parameters.

    COFFO control parameters. by Nebojsa Bacanin (13932723)

    Published 2022
    Subjects:
    Save to List
    Saved in:
  13. 33
    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:
  14. 34
    <i>hi</i>PRS algorithm process flow.

    <i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

    Published 2023
    Save to List
    Saved in:
  15. 35
    Confusion matrix for a binary outcome (adapted from Fawcett [30]).

    Confusion matrix for a binary outcome (adapted from Fawcett [30]). by João Albuquerque (12936572)

    Published 2022
    Save to List
    Saved in:
  16. 36
    RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values .

    RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values . by Jakub Stoklosa (3315042)

    Published 2023
    Save to List
    Saved in:
  17. 37
    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:
  18. 38
    The data processing and analysis pipeline.

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

    Published 2025
    Save to List
    Saved in:
  19. 39
    Analysis and design of algorithms for the manufacturing process of integrated circuits

    Analysis and design of algorithms for the manufacturing process of integrated circuits by Sonia Fleytas (16856403)

    Published 2023
    Save to List
    Saved in:
  20. 40
    An illustration and comparison of the fitness convergence curves for the Large-scale dataset (WaveformEW), medium-scale dataset (Zoo dataset), and Small-scale (Wine dataset) using 50 and 100 population sizes.

    An illustration and comparison of the fitness convergence curves for the Large-scale dataset (WaveformEW), medium-scale dataset (Zoo dataset), and Small-scale (Wine dataset) using... by Olaide N. Oyelade (14047002)

    Published 2023
    Subjects:
    Save to List
    Saved in:

Search Tools: