Showing 81 - 100 results of 12,381 for search '(((( algorithm i function ) OR ( algorithm sphere function ))) OR ( algorithm python function ))', query time: 0.88s Refine Results
  1. 81

    Comparative statistical performance of various algorithms in minimizing the <i>F</i> cost function. by Davut Izci (15927452)

    Published 2023
    “…<p>Comparative statistical performance of various algorithms in minimizing the <i>F</i> cost function.…”
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    CageCavityCalc (<i>C</i>3): A Computational Tool for Calculating and Visualizing Cavities in Molecular Cages by Vicente Martí-Centelles (1422415)

    Published 2024
    “…Efficiently predicting such properties is critical for accelerating the discovery of novel functional cages. Herein, we introduce <i>CageCavityCalc</i> (<i>C</i>3), a Python-based tool for calculating the cavity size of molecular cages. …”
  13. 93

    CageCavityCalc (<i>C</i>3): A Computational Tool for Calculating and Visualizing Cavities in Molecular Cages by Vicente Martí-Centelles (1422415)

    Published 2024
    “…Efficiently predicting such properties is critical for accelerating the discovery of novel functional cages. Herein, we introduce <i>CageCavityCalc</i> (<i>C</i>3), a Python-based tool for calculating the cavity size of molecular cages. …”
  14. 94

    CageCavityCalc (<i>C</i>3): A Computational Tool for Calculating and Visualizing Cavities in Molecular Cages by Vicente Martí-Centelles (1422415)

    Published 2024
    “…Efficiently predicting such properties is critical for accelerating the discovery of novel functional cages. Herein, we introduce <i>CageCavityCalc</i> (<i>C</i>3), a Python-based tool for calculating the cavity size of molecular cages. …”
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    Comparison of algorithm performance in ZDT1 and ZDT2 function tests. by Tao Dong (15551)

    Published 2025
    “…<p>Comparison of algorithm performance in ZDT1 and ZDT2 function tests.…”
  19. 99

    <i>K</i>-CDFs: A Nonparametric Clustering Algorithm via Cumulative Distribution Function by Jicai Liu (11419050)

    Published 2022
    “…<p>We propose a novel partitioning clustering procedure based on the cumulative distribution function (CDF), called <i>K</i>-CDFs. For univariate data, the <i>K</i>-CDFs represent the cluster centers by empirical CDFs and assign each observation to the closest center measured by the Cram<math><mrow><mi>e</mi><mo>´</mo></mrow></math>r-von Mises distance. …”
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