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Showing 61 - 80 results of 13,191 for search '(((( algorithm used functions ) OR ( algorithm phase function ))) OR ( algorithm python function ))', query time: 0.45s Refine Results
  1. 61
    (a): These systems were simulated for (0,3] and (0,3] without the prior knowledge about different phases, and the probability density function of points in feature space illustrates the dense areas as lighter color with a contour-plot.

    (a): These systems were simulated for (0,3] and (0,3] without the prior knowledge about different phases, and the probability density function of points in feature space illustrate... by Ali Talebi (7164203)

    Published 2025
    “…(b): The dense areas are separated by removing the data less than threshold = 0.5 in the probability density function. (c): The centroid of each cluster is determined by the K-means algorithm.…”
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  2. 62
    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. 63
    Histograms of the variables used in this study.

    Histograms of the variables used in this study. by Tuan Anh Pham (1346049)

    Published 2020
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  4. 64
    The control algorithm of MPC for SSI.

    The control algorithm of MPC for SSI. by Ahmed Abdelaleem (19066115)

    Published 2024
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  5. 65
    Cost functions implemented in Neuroptimus.

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

    Published 2024
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  6. 66
    Summary statistics for the number of function evaluations on real-world dataset—Phase I.

    Summary statistics for the number of function evaluations on real-world dataset—Phase I. by Fadi K. Dib (5204807)

    Published 2023
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  7. 67
    Summary statistics for the values of objective function on real-world dataset—Phase II.

    Summary statistics for the values of objective function on real-world dataset—Phase II. by Fadi K. Dib (5204807)

    Published 2023
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  8. 68
    Summary statistics for the values of objective function on real-world dataset—Phase I.

    Summary statistics for the values of objective function on real-world dataset—Phase I. by Fadi K. Dib (5204807)

    Published 2023
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  9. 69
    Summary statistics for the number of function evaluations on real-world dataset—Phase III.

    Summary statistics for the number of function evaluations on real-world dataset—Phase III. by Fadi K. Dib (5204807)

    Published 2023
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  10. 70
    Framework of the proposed algorithm.

    Framework of the proposed algorithm. by Jia Li (160557)

    Published 2025
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  11. 71
    Design and implementation of DelaySSA. The input data for DelaySSA are reaction information, initial states, parameters and delays. Combining these into the simulation function, the temporal molecular states <i>n</i> at specific time <i>t</i> will be generated for further visualization.

    Design and implementation of DelaySSA. The input data for DelaySSA are reaction information, initial states, parameters and delays. Combining these into the simulation function, th... by Ziyan Jin (21021976)

    Published 2025
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  12. 72
    Python implementation of the Trajectory Adaptive Multilevel Sampling algorithm for rare events and improvements

    Python implementation of the Trajectory Adaptive Multilevel Sampling algorithm for rare events and improvements by Pascal Wang (10130612)

    Published 2021
    “…</div><div><br></div><div>The `TAMS` folder contains the necessary files to run the TAMS algorithm. The `main.py` file is the file to be executed using a command of the type `python main.py`. …”
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  13. 73
    Parameters tuning using the model using the GA-DLNN model with 4 and 10 inputs.

    Parameters tuning using the model using the GA-DLNN model with 4 and 10 inputs. by Tuan Anh Pham (1346049)

    Published 2020
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  14. 74
    Multidimensional test results of BWEMFO and MFO on IEEE CEC 2017 test functions.

    Multidimensional test results of BWEMFO and MFO on IEEE CEC 2017 test functions. by Jingjing Ma (419752)

    Published 2025
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  15. 75
    Comparison between simulations for all algorithms and for all cases (1, 2 and 3).

    Comparison between simulations for all algorithms and for all cases (1, 2 and 3). by Rutinaldo Aguiar Nascimento (14259594)

    Published 2022
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  16. 76
    One iteration of the NSGA-II algorithm.

    One iteration of the NSGA-II algorithm. by Erick Axel Padilla-García (16839233)

    Published 2023
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  17. 77
    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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  18. 78
    A bar chart for the values of objective function on real-world dataset—Phase I.

    A bar chart for the values of objective function on real-world dataset—Phase I. by Fadi K. Dib (5204807)

    Published 2023
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  19. 79
    A bar chart for the values of objective function on real-world dataset—Phase II.

    A bar chart for the values of objective function on real-world dataset—Phase II. by Fadi K. Dib (5204807)

    Published 2023
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  20. 80
    A bar chart for the number of function evaluations on real-world dataset—Phase III.

    A bar chart for the number of function evaluations on real-world dataset—Phase III. by Fadi K. Dib (5204807)

    Published 2023
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