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competing optimization » routing optimization (Expand Search), cooperative optimization (Expand Search), composition optimization (Expand Search)
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Showing 1 - 20 results of 154 for search '(( binary based competing optimization algorithm ) OR ( binary _ process optimization algorithm ))*', query time: 0.73s Refine Results
  1. 1
    Feature selection convergence time comparison of various binary metaheuristic algorithms.

    Feature selection convergence time comparison of various binary metaheuristic algorithms. by Amal H. Alharbi (21755906)

    Published 2025
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  2. 2
    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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  3. 3
    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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  4. 4
    Feature selection ratio results for tested algorithms.

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

    Published 2022
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  5. 5
    Best fitness value results for tested algorithms.

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

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

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

    Published 2022
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  7. 7
    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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  8. 8
    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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  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
    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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  11. 11
    Schematic of iteration process of IDE-IIGA.

    Schematic of iteration process of IDE-IIGA. by Ling Zhao (111365)

    Published 2025
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  12. 12
    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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  13. 13
    Feature selection process.

    Feature selection process. by Balraj Preet Kaur (20370832)

    Published 2024
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  14. 14
    Histograms of various water quality parameters, including pH, Hardness, Solids, Chloramines, Sulfate, Organic Carbon, Trihalomethanes, Turbidity, and a binary portability check.

    Histograms of various water quality parameters, including pH, Hardness, Solids, Chloramines, Sulfate, Organic Carbon, Trihalomethanes, Turbidity, and a binary portability check. by Amal H. Alharbi (21755906)

    Published 2025
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  15. 15
    Proposed Algorithm.

    Proposed Algorithm. by Hend Bayoumi (22693738)

    Published 2025
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  16. 16
    Homomorphic binary tree.

    Homomorphic binary tree. by Jianhua He (341366)

    Published 2024
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  17. 17
    <i>hi</i>PRS algorithm process flow.

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

    Published 2023
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  18. 18
    Parameter settings of the comparison algorithms.

    Parameter settings of the comparison algorithms. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  19. 19
    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
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  20. 20
    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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