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Showing 41 - 60 results of 108 for search '(( binary plot design optimization algorithm ) OR ( binary data process optimization algorithm ))', query time: 0.52s Refine Results
  1. 41
    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
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  2. 42
    Medium-scale dataset comparative analysis using fitness and cost values for population size 50 and 100.

    Medium-scale dataset comparative analysis using fitness and cost values for population size 50 and 100. by Olaide N. Oyelade (14047002)

    Published 2023
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  3. 43
    Large-scale dataset comparative analysis using computation resources.

    Large-scale dataset comparative analysis using computation resources. by Olaide N. Oyelade (14047002)

    Published 2023
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  4. 44
    Datasets and their properties.

    Datasets and their properties. by Olaide N. Oyelade (14047002)

    Published 2023
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  5. 45
    An illustration and comparison of the cost 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 cost convergence curves for the Large-scale dataset (WaveformEW), medium-scale dataset (Zoo dataset), and Small-scale (Wine dataset) using 50... by Olaide N. Oyelade (14047002)

    Published 2023
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  6. 46
    Small-scale dataset comparative analysis using fitness and cost values for population sizes 50 and 100.

    Small-scale dataset comparative analysis using fitness and cost values for population sizes 50 and 100. by Olaide N. Oyelade (14047002)

    Published 2023
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  7. 47
    Medium-scale dataset comparative analysis using the number of features selected.

    Medium-scale dataset comparative analysis using the number of features selected. by Olaide N. Oyelade (14047002)

    Published 2023
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  8. 48
    Small-scale dataset comparative analysis using classification accuracy for population sizes 50 and 100.

    Small-scale dataset comparative analysis using classification accuracy for population sizes 50 and 100. by Olaide N. Oyelade (14047002)

    Published 2023
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  9. 49
    Large-scale dataset comparative analysis using the number of features selected.

    Large-scale dataset comparative analysis using the number of features selected. by Olaide N. Oyelade (14047002)

    Published 2023
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  10. 50
    Medium-scale dataset comparative analysis using classification accuracy for population sizes 50 and 100.

    Medium-scale dataset comparative analysis using classification accuracy for population sizes 50 and 100. by Olaide N. Oyelade (14047002)

    Published 2023
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  11. 51
    Medium-scale dataset comparative analysis using computation resources.

    Medium-scale dataset comparative analysis using computation resources. by Olaide N. Oyelade (14047002)

    Published 2023
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  12. 52
    Large-scale dataset comparative analysis using fitness and cost values for population sizes 50 and 100.

    Large-scale dataset comparative analysis using fitness and cost values for population sizes 50 and 100. by Olaide N. Oyelade (14047002)

    Published 2023
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  13. 53
    Small-scale dataset comparative analysis using computation resources.

    Small-scale dataset comparative analysis using computation resources. by Olaide N. Oyelade (14047002)

    Published 2023
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  14. 54
    Small-scale dataset comparative analysis using the number of features selected.

    Small-scale dataset comparative analysis using the number of features selected. by Olaide N. Oyelade (14047002)

    Published 2023
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  15. 55
    Large-scale dataset comparative analysis using classification accuracy for population sizes 50 and 100.

    Large-scale dataset comparative analysis using classification accuracy for population sizes 50 and 100. by Olaide N. Oyelade (14047002)

    Published 2023
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  16. 56
    Parameter settings.

    Parameter settings. by Olaide N. Oyelade (14047002)

    Published 2023
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  17. 57
    Fig 2 -

    Fig 2 - by Olaide N. Oyelade (14047002)

    Published 2023
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  18. 58
    Hierarchical clustering to infer a binary tree with <i>K</i> = 4 sampled populations.

    Hierarchical clustering to infer a binary tree with <i>K</i> = 4 sampled populations. by Tristan Mary-Huard (3864)

    Published 2023
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  19. 59
    The flowchart of the proposed algorithm.

    The flowchart of the proposed algorithm. by Muhammad Ayyaz Sheikh (18610943)

    Published 2024
    “…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
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  20. 60
    Application of ABC SMC to the fitting of the binary flip with cusp model.

    Application of ABC SMC to the fitting of the binary flip with cusp model. by Elena Camacho-Aguilar (10906327)

    Published 2021
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