يعرض 141 - 160 نتائج من 2,151 نتيجة بحث عن '(( algorithm machine function ) OR ( ((algorithm python) OR (algorithm both)) function ))*', وقت الاستعلام: 0.32s تنقيح النتائج
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    Hierarchical regression results. حسب Muna Saleh (10775575)

    منشور في 2024
    الموضوعات:
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    SHAP values (impact on model output). حسب Muna Saleh (10775575)

    منشور في 2024
    الموضوعات:
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    The pseudocode for the NAFPSO algorithm. حسب Huichao Guo (14515171)

    منشور في 2025
    "…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"
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    PSO algorithm flowchart. حسب Huichao Guo (14515171)

    منشور في 2025
    "…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"
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    Cost function calculated by QA with different hyperparameters. حسب Takuro Matsuta (21608505)

    منشور في 2025
    الموضوعات: "…currently available algorithms…"
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    Cost function calculated by SA with different hyperparameters. حسب Takuro Matsuta (21608505)

    منشور في 2025
    الموضوعات: "…currently available algorithms…"
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    Enrichment results of gly-DEGs. حسب Ziyang Liu (242055)

    منشور في 2025
    الموضوعات:
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    Comparison of different algorithms. حسب Dawei Wang (471687)

    منشور في 2025
    "…A sophisticated optimization model has been developed to simulate the optimal operation of machinery, aiming to maximize equipment utilization efficiency while addressing the challenges posed by worker fatigue. An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …"
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