Search alternatives:
required optimization » guided optimization (Expand Search), resource optimization (Expand Search), feature optimization (Expand Search)
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
data required » data acquired (Expand Search)
dietary data » history data (Expand Search)
also driven » also derived (Expand Search)
Showing 1 - 20 results of 26 for search '(( binary also driven optimization algorithm ) OR ( dietary data required optimization algorithm ))', query time: 0.48s Refine Results
  1. 1
    Initial parameter settings for the optimization algorithms.

    Initial parameter settings for the optimization algorithms. by Doaa Sami Khafaga (21463870)

    Published 2025
    Save to List
    Saved in:
  2. 2
    Bar chart comparing the average fitness values of various feature selection algorithms.

    Bar chart comparing the average fitness values of various feature selection algorithms. by Doaa Sami Khafaga (21463870)

    Published 2025
    Save to List
    Saved in:
  3. 3
    Box plots with swarm overlays for six feature selection algorithms, annotated with mean and standard deviation values.

    Box plots with swarm overlays for six feature selection algorithms, annotated with mean and standard deviation values. by Doaa Sami Khafaga (21463870)

    Published 2025
    Save to List
    Saved in:
  4. 4
    Line plots showing performance trends for six evaluation metrics across CNN combined with different bio-inspired optimization algorithms.

    Line plots showing performance trends for six evaluation metrics across CNN combined with different bio-inspired optimization algorithms. by Doaa Sami Khafaga (21463870)

    Published 2025
    Save to List
    Saved in:
  5. 5
    Correlation heatmap of performance scores among different feature selection algorithms: bOcOA, bPSO, bGWO, bFA, bGA, and bWAO.

    Correlation heatmap of performance scores among different feature selection algorithms: bOcOA, bPSO, bGWO, bFA, bGA, and bWAO. by Doaa Sami Khafaga (21463870)

    Published 2025
    Save to List
    Saved in:
  6. 6
    Density distribution plot of performance metrics for various feature selection algorithms: bOcOA, bPSO, bGWO, bFA, bGA, and bWAO.

    Density distribution plot of performance metrics for various feature selection algorithms: bOcOA, bPSO, bGWO, bFA, bGA, and bWAO. by Doaa Sami Khafaga (21463870)

    Published 2025
    Save to List
    Saved in:
  7. 7
    Classification baseline performance.

    Classification baseline performance. by Doaa Sami Khafaga (21463870)

    Published 2025
    Save to List
    Saved in:
  8. 8
    Feature selection results.

    Feature selection results. by Doaa Sami Khafaga (21463870)

    Published 2025
    Save to List
    Saved in:
  9. 9
    ANOVA test result.

    ANOVA test result. by Doaa Sami Khafaga (21463870)

    Published 2025
    Save to List
    Saved in:
  10. 10
    Summary of literature review.

    Summary of literature review. by Doaa Sami Khafaga (21463870)

    Published 2025
    Save to List
    Saved in:
  11. 11
    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. …”
    Save to List
    Saved in:
  12. 12
    DataSheet1_Evolutionary algorithm for the optimization of meal intake and insulin administration in patients with type 2 diabetes.PDF

    DataSheet1_Evolutionary algorithm for the optimization of meal intake and insulin administration in patients with type 2 diabetes.PDF by Eva Gonzalez-Flo (5046737)

    Published 2023
    Save to List
    Saved in:
  13. 13
    the functioning of BRPSO.

    the functioning of BRPSO. by Hossein Jarrahi (22530251)

    Published 2025
    “…A sensitivity analysis of key RFD parameters, including frictional moment and rigid beam length, highlights their influence on seismic performance. The optimization problem is formulated based on the seismic energy dissipation concept, employing a modified binary and real-coded particle swarm optimization (BRPSO) algorithm. …”
    Save to List
    Saved in:
  14. 14
    Characteristic of 6- and 10-story SMRF [99,98].

    Characteristic of 6- and 10-story SMRF [99,98]. by Hossein Jarrahi (22530251)

    Published 2025
    “…A sensitivity analysis of key RFD parameters, including frictional moment and rigid beam length, highlights their influence on seismic performance. The optimization problem is formulated based on the seismic energy dissipation concept, employing a modified binary and real-coded particle swarm optimization (BRPSO) algorithm. …”
    Save to List
    Saved in:
  15. 15
    The RFD’s behavior mechanism (2002).

    The RFD’s behavior mechanism (2002). by Hossein Jarrahi (22530251)

    Published 2025
    “…A sensitivity analysis of key RFD parameters, including frictional moment and rigid beam length, highlights their influence on seismic performance. The optimization problem is formulated based on the seismic energy dissipation concept, employing a modified binary and real-coded particle swarm optimization (BRPSO) algorithm. …”
    Save to List
    Saved in:
  16. 16
    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. …”
    Save to List
    Saved in:
  17. 17
    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. …”
    Save to List
    Saved in:
  18. 18
    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. …”
    Save to List
    Saved in:
  19. 19
    Data_Sheet_1_Bi-objective goal programming for balancing costs vs. nutritional adequacy.pdf

    Data_Sheet_1_Bi-objective goal programming for balancing costs vs. nutritional adequacy.pdf by Melissa F. Koenen (14262764)

    Published 2022
    Save to List
    Saved in:
  20. 20
    Data_Sheet_1_Bi-objective goal programming for balancing costs vs. nutritional adequacy.pdf

    Data_Sheet_1_Bi-objective goal programming for balancing costs vs. nutritional adequacy.pdf by Melissa F. Koenen (14262764)

    Published 2023
    Save to List
    Saved in:

Search Tools: