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Showing 81 - 100 results of 2,748 for search '(((( algorithm l function ) OR ( algorithm phase functions ))) OR ( algorithm python function ))', query time: 0.56s Refine Results
  1. 81
    Summary statistics for the values of objective function—Phase II.

    Summary statistics for the values of objective function—Phase II. by Fadi K. Dib (5204807)

    Published 2023
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  2. 82
    Summary statistics for the number of function evaluations—Phase I.

    Summary statistics for the number of function evaluations—Phase I. by Fadi K. Dib (5204807)

    Published 2023
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  3. 83
    Summary statistics for the number of function evaluations—Phase III.

    Summary statistics for the number of function evaluations—Phase III. by Fadi K. Dib (5204807)

    Published 2023
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  4. 84
    Approximate energy consumed per particles in <i>nano Joules</i> (<i>nJ</i>) for various computation platforms and algorithms (A: first algorithm, B: second algorithm, C: third algorithm: and D: fourth algorithm).

    Approximate energy consumed per particles in <i>nano Joules</i> (<i>nJ</i>) for various computation platforms and algorithms (A: first algorithm, B: second algorithm, C: third algo... by Abedalmuhdi Almomany (18547669)

    Published 2024
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  5. 85
    Function <i>χ</i><sub><i>opt</i></sub> superimposed with the phase-field function indicating the channel geometry.

    Function <i>χ</i><sub><i>opt</i></sub> superimposed with the phase-field function indicating the channel geometry. by Martina Bukač (20161460)

    Published 2024
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  6. 86
    Example of landmark registration to align ‘peaks’ of high density in the probability density function (PDF) of CD4 expression on blood T cells for a target distribution and chosen reference.

    Example of landmark registration to align ‘peaks’ of high density in the probability density function (PDF) of CD4 expression on blood T cells for a target distribution and chosen... by Ross J. Burton (10941910)

    Published 2021
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  7. 87
    TV-BayesOpt algorithm performance for tracking a superimposed (gradual and periodic) drift in the optimal stimulation phase for phase-locked stimulation, <i>ψ</i>*.

    TV-BayesOpt algorithm performance for tracking a superimposed (gradual and periodic) drift in the optimal stimulation phase for phase-locked stimulation, <i>ψ</i>*. by John E. Fleming (8533956)

    Published 2023
    “…For each estimated GPR the confidence bounds observed at the predicted optimal phase value are small and become larger for values further away from this value due to the algorithm’s acquisition function prioritizing exploitation of the parameter space during the optimization process.…”
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  8. 88
    Functional effect prediction of FUS mutations by ten nsSNP prediction algorithms.

    Functional effect prediction of FUS mutations by ten nsSNP prediction algorithms. by L. F. S. Bonet (11502082)

    Published 2021
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  9. 89
    Convergence curve of reactive power transmission line loss minimization based on (a) the HFPSO algorithm and (b) the PSO algorithm.

    Convergence curve of reactive power transmission line loss minimization based on (a) the HFPSO algorithm and (b) the PSO algorithm. by Abdullah Khan (377292)

    Published 2020
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  10. 90
    Convergence curve of real power transmission line loss minimization by using (a) the HFPSO algorithm and (b) the PSO algorithm.

    Convergence curve of real power transmission line loss minimization by using (a) the HFPSO algorithm and (b) the PSO algorithm. by Abdullah Khan (377292)

    Published 2020
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  11. 91
    Simulations details for the Rosenbrock function.

    Simulations details for the Rosenbrock function. by Rutinaldo Aguiar Nascimento (14259594)

    Published 2022
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  12. 92
    Simulations details for the Rastrigin function.

    Simulations details for the Rastrigin function. by Rutinaldo Aguiar Nascimento (14259594)

    Published 2022
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  13. 93
    The probability density function of points in feature space of variance versus mean of the local field for (0,3] and (0,3] displayed as a contour-plot.

    The probability density function of points in feature space of variance versus mean of the local field for (0,3] and (0,3] displayed as a contour-plot. by Ali Talebi (7164203)

    Published 2025
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  14. 94
    Mean and STD obtained by eight enhanced DEs and DEGH on benchmark functions at 30D.

    Mean and STD obtained by eight enhanced DEs and DEGH on benchmark functions at 30D. by Xuxu Zhong (10099054)

    Published 2021
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  15. 95
    Mean and STD obtained by eight enhanced DEs and DEGH on benchmark functions at 100D.

    Mean and STD obtained by eight enhanced DEs and DEGH on benchmark functions at 100D. by Xuxu Zhong (10099054)

    Published 2021
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  16. 96
    Mean and STD obtained by eight enhanced DEs and DEGH on benchmark functions at 50D.

    Mean and STD obtained by eight enhanced DEs and DEGH on benchmark functions at 50D. by Xuxu Zhong (10099054)

    Published 2021
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  17. 97
    A bar chart for the values of objective function—Phase I.

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

    Published 2023
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  18. 98
    A bar chart for the number of function evaluations—Phase I.

    A bar chart for the number of function evaluations—Phase I. by Fadi K. Dib (5204807)

    Published 2023
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  19. 99
    A bar chart for the values of objective function—Phase II.

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

    Published 2023
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  20. 100
    A bar chart for the number of function evaluations—Phase III.

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

    Published 2023
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