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Showing 1 - 20 results of 398 for search '(((( complement box algorithm ) OR ( elements control algorithm ))) OR ( level coding algorithm ))', query time: 0.47s Refine Results
  1. 1
    Main code.

    Main code. by Jingguo Bi (21439766)

    Published 2025
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  2. 2
    Schematic diagram of elements in the delivery area.

    Schematic diagram of elements in the delivery area. by Yingbo Mao (22522192)

    Published 2025
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  3. 3
    Pseudo-code of large neighborhood search (<i>LNS</i>) algorithm.

    Pseudo-code of large neighborhood search (<i>LNS</i>) algorithm. by Jiren CAO (20442214)

    Published 2024
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  4. 4
    Computational Domain: The computational domain was discretized using conformal tetrahedral elements, resulting in a total of 926K elements.

    Computational Domain: The computational domain was discretized using conformal tetrahedral elements, resulting in a total of 926K elements. by Martina Bukač (20161460)

    Published 2024
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  5. 5
    Chromosome coding.

    Chromosome coding. by Junjie He (700642)

    Published 2024
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  6. 6
    Open-source code for the Spatial Optimization Model for Land Use (SSFLA-MLAS)

    Open-source code for the Spatial Optimization Model for Land Use (SSFLA-MLAS) by bowen pang (21837359)

    Published 2025
    “…<p dir="ltr">The open-source content is the source code of a land use spatial optimization model (SSFLA-MLAS) that couples the spatial leapfrog algorithm with multi-level multi-agent systems. …”
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  7. 7
    The ranking of algorithms with MPTM mutation by TOPSIS.

    The ranking of algorithms with MPTM mutation by TOPSIS. by Jalal- ud-Din (21474307)

    Published 2025
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  8. 8
    The ranking of algorithms with NUM mutation by TOPSIS.

    The ranking of algorithms with NUM mutation by TOPSIS. by Jalal- ud-Din (21474307)

    Published 2025
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  9. 9
    The ranking of algorithms with PM mutation by TOPSIS.

    The ranking of algorithms with PM mutation by TOPSIS. by Jalal- ud-Din (21474307)

    Published 2025
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  10. 10
    Visual line representation of algorithms with NUM mutation.

    Visual line representation of algorithms with NUM mutation. by Jalal- ud-Din (21474307)

    Published 2025
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  11. 11
    Visual line representation of algorithm with PM mutation.

    Visual line representation of algorithm with PM mutation. by Jalal- ud-Din (21474307)

    Published 2025
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  12. 12
    Visual representation of ranks of algorithms with PM mutation.

    Visual representation of ranks of algorithms with PM mutation. by Jalal- ud-Din (21474307)

    Published 2025
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  13. 13
    Visual performance of each algorithm with PM mutation.

    Visual performance of each algorithm with PM mutation. by Jalal- ud-Din (21474307)

    Published 2025
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  14. 14
    Visual performance of each algorithm with MPTM mutation.

    Visual performance of each algorithm with MPTM mutation. by Jalal- ud-Din (21474307)

    Published 2025
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  15. 15
    Visual line representation of algorithm with MPTM mutation.

    Visual line representation of algorithm with MPTM mutation. by Jalal- ud-Din (21474307)

    Published 2025
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  16. 16
    Visual performance of each algorithm with NUM mutation.

    Visual performance of each algorithm with NUM mutation. by Jalal- ud-Din (21474307)

    Published 2025
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  17. 17
    Visual representation of ranks of algorithms with MPTM mutation.

    Visual representation of ranks of algorithms with MPTM mutation. by Jalal- ud-Din (21474307)

    Published 2025
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  18. 18
    Visual representation of ranks of algorithms with NUM mutation.

    Visual representation of ranks of algorithms with NUM mutation. by Jalal- ud-Din (21474307)

    Published 2025
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  19. 19
    Visual parametric framework for all fifteen algorithms.

    Visual parametric framework for all fifteen algorithms. by Jalal- ud-Din (21474307)

    Published 2025
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  20. 20
    Convergence curve of the DBO algorithm.

    Convergence curve of the DBO algorithm. by Ma Haohao (22177538)

    Published 2025
    “…The improved Dung Beetle Optimization algorithm, Back Propagation Neural Network, Finite Element Analysis, and Response Surface Methodology provide a strong guarantee for the selection of robot polishing process parameters. …”
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