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feature optimization » resource optimization (Expand Search), feature elimination (Expand Search), structure optimization (Expand Search)
based optimization » whale optimization (Expand Search)
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Showing 61 - 80 results of 270 for search '(( binary data feature optimization algorithm ) OR ( binary base based optimization algorithm ))', query time: 0.57s Refine Results
  1. 61
    Comparison in terms of the sensitivity.

    Comparison in terms of the sensitivity. 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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  2. 62
    Parameter sensitivity of BIMGO.

    Parameter sensitivity of BIMGO. 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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  3. 63
    Details of the medical datasets.

    Details of the medical datasets. 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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  4. 64
    The flowchart of IMGO.

    The flowchart of IMGO. 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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  5. 65
    Iterative chart of control factor.

    Iterative chart of control factor. 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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  6. 66
    Details of 23 basic benchmark functions.

    Details of 23 basic benchmark functions. 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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  7. 67
    Related researches.

    Related researches. 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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  8. 68
    S1 Dataset -

    S1 Dataset - 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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  9. 69
    CEC 2019 benchmark characteristics.

    CEC 2019 benchmark characteristics. by Nebojsa Bacanin (13932723)

    Published 2022
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  10. 70
    Results of Holm’s step-down procedure.

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

    Published 2022
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  11. 71
    Friedman ranks of tested methods on CEC2019 benchmark functions.

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

    Published 2022
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  12. 72
    V-shaped transfer functions.

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

    Published 2022
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  13. 73
    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
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  14. 74
    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
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  15. 75
    Error rate convergence graphs.

    Error rate convergence graphs. by Nebojsa Bacanin (13932723)

    Published 2022
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  16. 76
    COVID-19 dataset description.

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

    Published 2022
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  17. 77
    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
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  18. 78
    COFFO control parameters.

    COFFO control parameters. by Nebojsa Bacanin (13932723)

    Published 2022
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  19. 79
    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
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  20. 80
    IRBMO vs. variant comparison adaptation data.

    IRBMO vs. variant comparison adaptation data. 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. …”
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