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function optimization » reaction optimization (Expand Search), formulation optimization (Expand Search), generation optimization (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
change function » hand function (Expand Search), change action (Expand Search), change detection (Expand Search)
binary change » binary image (Expand Search)
lines based » lens based (Expand Search), genes based (Expand Search), lines used (Expand Search)
based wolf » based whole (Expand Search), based work (Expand Search), based well (Expand Search)
Showing 1 - 16 results of 16 for search '(( binary change function optimization algorithm ) OR ( lines based wolf optimization algorithm ))', query time: 0.54s Refine Results
  1. 1
    The confidence change of the binary image after iteration.

    The confidence change of the binary image after iteration. by Dingming Yang (8505990)

    Published 2022
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  2. 2
    Performance on GradEva.

    Performance on GradEva. by Jamilu Yahaya (18563445)

    Published 2024
    “…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …”
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  3. 3
    The considered test problems.

    The considered test problems. by Jamilu Yahaya (18563445)

    Published 2024
    “…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …”
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  4. 4
    Performance on FunEva.

    Performance on FunEva. by Jamilu Yahaya (18563445)

    Published 2024
    “…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …”
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  5. 5
    Performance on Iter.

    Performance on Iter. by Jamilu Yahaya (18563445)

    Published 2024
    “…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …”
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  6. 6
    Continuation of Table 2.

    Continuation of Table 2. by Jamilu Yahaya (18563445)

    Published 2024
    “…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …”
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  7. 7
    Unraveling Adsorbate-Induced Structural Evolution of Iron Carbide Nanoparticles

    Unraveling Adsorbate-Induced Structural Evolution of Iron Carbide Nanoparticles by Peter S. Rice (11805875)

    Published 2025
    “…Here, using a combined density functional theory (DFT), neural network interatomic potential-assisted global optimization, and ensemble learning study, we evaluate dynamic surface changes associated with syngas (H and CO) interactions. …”
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  8. 8
    Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield and Amygdala Volume of Structural MRI.pdf

    Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield... by Uttam Khatri (12689072)

    Published 2022
    “…Finally, we implemented and compared the different feature selection algorithms to integrate the structural features, brain networks, and voxel features to optimize the diagnostic identifications of AD using support vector machine (SVM) classifiers. …”
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  9. 9
    Table_1_Distinguishing HapMap Accessions Through Recursive Set Partitioning in Hierarchical Decision Trees.pdf

    Table_1_Distinguishing HapMap Accessions Through Recursive Set Partitioning in Hierarchical Decision Trees.pdf by Wenchao Zhang (1324959)

    Published 2021
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  10. 10
    Table_2_Distinguishing HapMap Accessions Through Recursive Set Partitioning in Hierarchical Decision Trees.pdf

    Table_2_Distinguishing HapMap Accessions Through Recursive Set Partitioning in Hierarchical Decision Trees.pdf by Wenchao Zhang (1324959)

    Published 2021
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  11. 11
    Presentation_1_Distinguishing HapMap Accessions Through Recursive Set Partitioning in Hierarchical Decision Trees.pdf

    Presentation_1_Distinguishing HapMap Accessions Through Recursive Set Partitioning in Hierarchical Decision Trees.pdf by Wenchao Zhang (1324959)

    Published 2021
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  12. 12
    Table_3_Distinguishing HapMap Accessions Through Recursive Set Partitioning in Hierarchical Decision Trees.pdf

    Table_3_Distinguishing HapMap Accessions Through Recursive Set Partitioning in Hierarchical Decision Trees.pdf by Wenchao Zhang (1324959)

    Published 2021
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  13. 13
    Data_Sheet_1_Distinguishing HapMap Accessions Through Recursive Set Partitioning in Hierarchical Decision Trees.zip

    Data_Sheet_1_Distinguishing HapMap Accessions Through Recursive Set Partitioning in Hierarchical Decision Trees.zip by Wenchao Zhang (1324959)

    Published 2021
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  14. 14
    Image_1_Distinguishing HapMap Accessions Through Recursive Set Partitioning in Hierarchical Decision Trees.tif

    Image_1_Distinguishing HapMap Accessions Through Recursive Set Partitioning in Hierarchical Decision Trees.tif by Wenchao Zhang (1324959)

    Published 2021
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  15. 15
    Data_Sheet_3_Distinguishing HapMap Accessions Through Recursive Set Partitioning in Hierarchical Decision Trees.zip

    Data_Sheet_3_Distinguishing HapMap Accessions Through Recursive Set Partitioning in Hierarchical Decision Trees.zip by Wenchao Zhang (1324959)

    Published 2021
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  16. 16
    Data_Sheet_2_Distinguishing HapMap Accessions Through Recursive Set Partitioning in Hierarchical Decision Trees.zip

    Data_Sheet_2_Distinguishing HapMap Accessions Through Recursive Set Partitioning in Hierarchical Decision Trees.zip by Wenchao Zhang (1324959)

    Published 2021
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