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Showing 41 - 60 results of 5,183 for search '(((( algorithm value function ) OR ( algorithm wave function ))) OR ( algorithm python function ))', query time: 0.68s Refine Results
  1. 41
    <b>Opti2Phase</b>: Python scripts for two-stage focal reducer

    <b>Opti2Phase</b>: Python scripts for two-stage focal reducer by Morgan Najera (21540776)

    Published 2025
    “…</li></ul><p dir="ltr">The scripts rely on the following Python packages. Where available, repository links are provided:</p><ol><li><b>NumPy</b>, version 1.22.1</li><li><b>SciPy</b>, version 1.7.3</li><li><b>PyGAD</b>, version 3.0.1 — https://pygad.readthedocs.io/en/latest/#</li><li><b>bees-algorithm</b>, version 1.0.2 — https://pypi.org/project/bees-algorithm</li><li><b>KrakenOS</b>, version 1.0.0.19 — https://github.com/Garchupiter/Kraken-Optical-Simulator</li><li><b>matplotlib</b>, version 3.5.2</li></ol><p dir="ltr">All scripts are modular and organized to reflect the design stages described in the manuscript.…”
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  2. 42
    The figures showed a comparison of the balanced and imbalanced sequences and performance of classifiers.

    The figures showed a comparison of the balanced and imbalanced sequences and performance of classifiers. by Solomon Shiferaw Beyene (9143178)

    Published 2020
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  3. 43
    Definitions of global parameters used for constructing random ecosystems.

    Definitions of global parameters used for constructing random ecosystems. by Robert Marsland (8616483)

    Published 2020
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  4. 44
    Objective function values of different algorithms on individual problem instances.

    Objective function values of different algorithms on individual problem instances. by Panfei Li (22379086)

    Published 2025
    “…<p>Objective function values of different algorithms on individual problem instances.…”
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  5. 45
    Loss function values of target detection algorithms during training.

    Loss function values of target detection algorithms during training. by Guodong Su (7876934)

    Published 2024
    “…<p>Loss function values of target detection algorithms during training.…”
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  6. 46
    Sensor value scenario for average value algorithm.

    Sensor value scenario for average value algorithm. by Gourab Saha (8987405)

    Published 2025
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  7. 47
    Initialization parameter values for the comparison algorithms.

    Initialization parameter values for the comparison algorithms. by Muhammad Zubair Rehman (11243478)

    Published 2021
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  8. 48
    Predictions from a Universal Value Function Approximator (UVFA) algorithm.

    Predictions from a Universal Value Function Approximator (UVFA) algorithm. by Sam Hall-McMaster (10343795)

    Published 2025
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  9. 49
    Performance profile of the four algorithms based on the function value of iteration number.

    Performance profile of the four algorithms based on the function value of iteration number. by Sulaiman M. Ibrahim (20614376)

    Published 2025
    “…<p>Performance profile of the four algorithms based on the function value of iteration number.…”
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  10. 50
    GD and IGD values of the traditional NSGA-II algorithm.

    GD and IGD values of the traditional NSGA-II algorithm. by Ying Wang (11406)

    Published 2024
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  11. 51
    GD and IGD values of the improved NSGA-II algorithm.

    GD and IGD values of the improved NSGA-II algorithm. by Ying Wang (11406)

    Published 2024
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  12. 52
    Objective function values of each algorithm for solving large-scale problems.

    Objective function values of each algorithm for solving large-scale problems. by Lijun Fan (2007628)

    Published 2023
    “…<p>Objective function values of each algorithm for solving large-scale problems.…”
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  13. 53
    Values of the fitness function for different algorithms run on various companies’ datasets.

    Values of the fitness function for different algorithms run on various companies’ datasets. by Bitanu Chatterjee (15295261)

    Published 2023
    “…<p>Values of the fitness function for different algorithms run on various companies’ datasets.…”
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  14. 54
    IGD values of different algorithms under different standard test functions.

    IGD values of different algorithms under different standard test functions. by Jun Sun (48981)

    Published 2023
    “…<p>IGD values of different algorithms under different standard test functions.…”
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  15. 55
    Critical values of membership functions learned from the study cohort by the algorithm.

    Critical values of membership functions learned from the study cohort by the algorithm. by Yufeng Zhang (195768)

    Published 2023
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  16. 56
    The obtained cost function values with respect to each run of different algorithms.

    The obtained cost function values with respect to each run of different algorithms. by Davut Izci (15927452)

    Published 2023
    “…<p>The obtained cost function values with respect to each run of different algorithms.…”
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  17. 57
    (a) Radar chart of these algorithms (23 Benchmark functions), (b) The sorting diagram of these algorithms (23 Benchmark functions).

    (a) Radar chart of these algorithms (23 Benchmark functions), (b) The sorting diagram of these algorithms (23 Benchmark functions). by Yu Liu (6938)

    Published 2025
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  18. 58
    S1 File -

    S1 File - by Yuh-Chin T. Huang (17867207)

    Published 2024
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  19. 59
    S1 Dataset -

    S1 Dataset - by Yuh-Chin T. Huang (17867207)

    Published 2024
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  20. 60
    Comparison of PSNR values of different algorithms.

    Comparison of PSNR values of different algorithms. by Xiaojun Wang (50332)

    Published 2025
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