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Showing 21 - 40 results of 9,422 for search '(( ((algorithm informed) OR (algorithm before)) function ) OR ( algorithm python function ))*', query time: 0.52s Refine Results
  1. 21
    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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  2. 22
    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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  3. 23
    The topology of the NYN.

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

    Published 2022
    Subjects: “…evolutionary genetic algorithm…”
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  4. 24
    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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  5. 25
    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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  6. 26
    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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  7. 27
    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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  8. 28
    The topology of HN.

    The topology of HN. by Yi Tao (178829)

    Published 2022
    Subjects: “…evolutionary genetic algorithm…”
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  9. 29
    The losses of the training process before and after the optimization of loss function.

    The losses of the training process before and after the optimization of loss function. by Peihan Wen (6324315)

    Published 2022
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  10. 30
    Comparison of loss function curves before and after improvement.

    Comparison of loss function curves before and after improvement. by Xiaozhou Feng (2918222)

    Published 2025
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  11. 31
    Skeletonisation algorithm.

    Skeletonisation algorithm. by Jordan Hembrow (16908051)

    Published 2023
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  12. 32
    Parameters of the genetic algorithm.

    Parameters of the genetic algorithm. by Jian Ma (170138)

    Published 2025
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  13. 33
    Cost functions implemented in Neuroptimus.

    Cost functions implemented in Neuroptimus. by Máté Mohácsi (20469514)

    Published 2024
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  14. 34
    Comparison of model feature extraction before and after adding SPDConv.

    Comparison of model feature extraction before and after adding SPDConv. by Jia Li (160557)

    Published 2025
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  15. 35
    Pseudo-code of MWOA algorithm.

    Pseudo-code of MWOA algorithm. by Yi-Qiang Xia (20161326)

    Published 2024
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  16. 36
    Path comparison before and after smoothing.

    Path comparison before and after smoothing. by Zhenggang Wang (1753657)

    Published 2025
    Subjects: “…target gravitational function…”
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  17. 37
    Comparison before and after path pruning.

    Comparison before and after path pruning. by Zhenggang Wang (1753657)

    Published 2025
    Subjects: “…target gravitational function…”
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  18. 38
    The structure of genetic algorithm (GA).

    The structure of genetic algorithm (GA). by Ali Akbar Moosavi (17769033)

    Published 2024
    “…First, physico-chemical inputs as bulk density (BD), initial water content (W<sub>i</sub>), saturated water content (W<sub>s</sub>), mean weight diameter (MWD), and geometric mean diameter (GMD) of aggregates, pH, electrical conductivity (EC), and calcium carbonate equivalent (CCE) were measured. Then, radial basis functions (RBFNNs), multilayer perceptron (MLPNNs), hybrid genetic algorithm (GA-NNs), and particle swarm optimization (PSO-NNs) neural networks were utilized to develop PTFs and compared their accuracy with the traditional regression model (MLR) using statistical indices. …”
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  19. 39
    Explained variance ration of the PCA algorithm.

    Explained variance ration of the PCA algorithm. by Abeer Aljohani (18497914)

    Published 2025
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  20. 40
    Comparison of model visualization before and after SPPFCSPC improvement.

    Comparison of model visualization before and after SPPFCSPC improvement. by Wenyuan Xu (2553028)

    Published 2025
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