Showing 41 - 60 results of 1,046 for search '(( element method algorithm ) OR ((( data encoding algorithm ) OR ( path finding algorithm ))))', query time: 0.56s Refine Results
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    Algorithm comparison. by Manxian Yang (20521600)

    Published 2025
    “…In the context of multi-machine scheduling, the BNSGA-III algorithm outperforms the NSGA-II, NSGA-III, and MOEA/D algorithms, achieving improvements in total travel distance (12.3% to 34.4%), path balance (60.9% to 66.2%), and workload distribution (78.7% to 92.9%). …”
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    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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    Element model generation method with geometric distribution errors by Yiqi Liu (21357815)

    Published 2025
    “…The product surface geometric distribution error is directly attached to the element nodes of the product ideal element model using the error surface reconstruction method and the replacement algorithm of the element node vector height based on the product’s point cloud data. …”
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    NSGA-III algorithm flow chart. by Manxian Yang (20521600)

    Published 2025
    “…In the context of multi-machine scheduling, the BNSGA-III algorithm outperforms the NSGA-II, NSGA-III, and MOEA/D algorithms, achieving improvements in total travel distance (12.3% to 34.4%), path balance (60.9% to 66.2%), and workload distribution (78.7% to 92.9%). …”
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    (HSCRC) encoding scheme. by R. Sakthivel (2589547)

    Published 2024
    “…<div><p>Loss-less data compression becomes the need of the hour for effective data compression and computation in VLSI test vector generation and testing in addition to hardware AI/ML computations. …”
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    Beluga Whale Optimization algorithm flow chart. by Manxian Yang (20521600)

    Published 2025
    “…In the context of multi-machine scheduling, the BNSGA-III algorithm outperforms the NSGA-II, NSGA-III, and MOEA/D algorithms, achieving improvements in total travel distance (12.3% to 34.4%), path balance (60.9% to 66.2%), and workload distribution (78.7% to 92.9%). …”