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Showing 41 - 60 results of 760 for search '(((( algorithm fc function ) OR ( algorithm pre function ))) OR ( algorithm python function ))', query time: 0.59s Refine Results
  1. 41
    Reward function related parameters.

    Reward function related parameters. by Honglei Pang (22693724)

    Published 2025
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  2. 42
    Example of the CNF function for off-axis DHM holograms recorded in a non-telecentric configuration.

    Example of the CNF function for off-axis DHM holograms recorded in a non-telecentric configuration. by Raul Castañeda (13932971)

    Published 2022
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  3. 43
    Search-based testing (Genetic Algorithm) - Chapter 11 of the book "Software Testing Automation"

    Search-based testing (Genetic Algorithm) - Chapter 11 of the book "Software Testing Automation" by Saeed Parsa (13893726)

    Published 2022
    “…</p> <p><br></p> <p>3. Algorithm</p> <p>Below is the main body of the test data generator program:</p> <p>  </p> <p>the main body of a Python program to generate test data for Python functions.…”
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  4. 44
    3D modeling qualities of the AS single-template models built by including DOPE in the objective function of MODELLER.

    3D modeling qualities of the AS single-template models built by including DOPE in the objective function of MODELLER. by Giacomo Janson (8138517)

    Published 2019
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  5. 45
    3D modeling qualities of the AM multiple-template models built by including DOPE in the objective function of MODELLER.

    3D modeling qualities of the AM multiple-template models built by including DOPE in the objective function of MODELLER. by Giacomo Janson (8138517)

    Published 2019
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  6. 46
    Information of nodes and pipes of NYN.

    Information of nodes and pipes of NYN. by Yi Tao (178829)

    Published 2022
    Subjects: “…evolutionary genetic algorithm…”
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  7. 47
    The topology of the NYN.

    The topology of the NYN. by Yi Tao (178829)

    Published 2022
    Subjects: “…evolutionary genetic algorithm…”
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  8. 48
    The result of Wilcoxon signed-rand test.

    The result of Wilcoxon signed-rand test. by Yi Tao (178829)

    Published 2022
    Subjects: “…evolutionary genetic algorithm…”
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  9. 49
    The Simulation and optimization process of pipe diameter selection.

    The Simulation and optimization process of pipe diameter selection. by Yi Tao (178829)

    Published 2022
    Subjects: “…evolutionary genetic algorithm…”
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  10. 50
    Optional pipe diameter and unit price of NYN.

    Optional pipe diameter and unit price of NYN. by Yi Tao (178829)

    Published 2022
    Subjects: “…evolutionary genetic algorithm…”
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  11. 51
    Optional pipe diameter and unit price of HN.

    Optional pipe diameter and unit price of HN. by Yi Tao (178829)

    Published 2022
    Subjects: “…evolutionary genetic algorithm…”
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  12. 52
    The topology of HN.

    The topology of HN. by Yi Tao (178829)

    Published 2022
    Subjects: “…evolutionary genetic algorithm…”
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  13. 53
    Information of nodes and pipes of HN.

    Information of nodes and pipes of HN. by Yi Tao (178829)

    Published 2022
    Subjects: “…evolutionary genetic algorithm…”
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  14. 54
    Practical rules for summing the series of the Tweedie probability density function with high-precision arithmetic

    Practical rules for summing the series of the Tweedie probability density function with high-precision arithmetic by NELSON L. DIAS (8078003)

    Published 2019
    “…With these practical rules, simple summation algorithms provide sufficiently robust results for the calculation of the density function and its definite integrals. …”
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  15. 55
    Sets of best performing parameters obtained after gridsearching through different values for each classification algorithm.

    Sets of best performing parameters obtained after gridsearching through different values for each classification algorithm. by Adhiraj Nath (17118269)

    Published 2023
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  16. 56
    HIV exposure risk algorithm. HIV exposure risk algorithm based on available data from the Tonse Padmozi trial.

    HIV exposure risk algorithm. HIV exposure risk algorithm based on available data from the Tonse Padmozi trial. by Anna M. Leone (22486372)

    Published 2025
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  17. 57
    Data of PV, WT, FC, and utilized coefficients.

    Data of PV, WT, FC, and utilized coefficients. by Obaid Aldosari (19797428)

    Published 2024
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  18. 58
    Average accuracy (across all 12 subject) as a function of the number of eigenvectors obtained with different dimensionality reduction techniques for the best classifier—k-NN (see also Table 3).

    Average accuracy (across all 12 subject) as a function of the number of eigenvectors obtained with different dimensionality reduction techniques for the best classifier—k-NN (see a... by Elnaz Lashgari (11278808)

    Published 2021
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  19. 59
    Fold Change (FC) in protein levels among non-survivors compared to survivors in 40 CERES participants.

    Fold Change (FC) in protein levels among non-survivors compared to survivors in 40 CERES participants. by Yue Ren (1311615)

    Published 2023
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  20. 60
    As for Fig 2, we present failure rates as a function of the cohort size (vertical axis) versus the number of distractors (horizontal axis), for the Smyth and McClave baseline algorithm from [76].

    As for Fig 2, we present failure rates as a function of the cohort size (vertical axis) versus the number of distractors (horizontal axis), for the Smyth and McClave baseline algor... by Daniela Huppenkothen (9174507)

    Published 2020
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