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Showing 61 - 80 results of 15,928 for search '(((( algorithm a function ) OR ( algorithms real function ))) OR ( algorithm python function ))', query time: 0.44s Refine Results
  1. 61
    PSO parameters and objective function.

    PSO parameters and objective function. by André G. Coimbra (21354135)

    Published 2025
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  2. 62
    GA parameters and objective function.

    GA parameters and objective function. by André G. Coimbra (21354135)

    Published 2025
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  3. 63
    Objective function values of the algorithms across individual problem instances grouped by scale: (a) Small, (b) Medium, (c) Large, (d) Super-Large.

    Objective function values of the algorithms across individual problem instances grouped by scale: (a) Small, (b) Medium, (c) Large, (d) Super-Large. by Panfei Li (22379086)

    Published 2025
    “…<p>Objective function values of the algorithms across individual problem instances grouped by scale: (a) Small, (b) Medium, (c) Large, (d) Super-Large.…”
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  4. 64
    Results of Wilcoxon signed-rank test for benchmark functions.

    Results of Wilcoxon signed-rank test for benchmark functions. by Serdar Ekinci (15927455)

    Published 2024
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  5. 65
    Comparative statistical results obtained against benchmark functions.

    Comparative statistical results obtained against benchmark functions. by Serdar Ekinci (15927455)

    Published 2024
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  6. 66
    RRMSE and SSIM values of reconstructed images by the proposed algorithms and the compared methods for the first and second study cases and the noisy data.

    RRMSE and SSIM values of reconstructed images by the proposed algorithms and the compared methods for the first and second study cases and the noisy data. by Mona Selim (12969227)

    Published 2022
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  7. 67
    Comparison of results of different algorithms.

    Comparison of results of different algorithms. by Zhibo Fu (19009854)

    Published 2024
    “…The Yolov8s-change model provides a fast, real-time and efficient detection solution for gangue sorting. …”
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  8. 68
    Estimation of the convergence of the algorithm for simulated ARGs of <i>L</i> leaves: VI distance to real MCCs as a function of the number of iterations of the SA optimization, scaled by <i>L</i>.

    Estimation of the convergence of the algorithm for simulated ARGs of <i>L</i> leaves: VI distance to real MCCs as a function of the number of iterations of the SA optimization, scaled by <i>L</i>. by Pierre Barrat-Charlaix (9556592)

    Published 2022
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  9. 69
    Parameters of the test function.

    Parameters of the test function. by Hao Zhang (15339)

    Published 2024
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  10. 70
    IEEE CEC 2017 benchmark function specifications.

    IEEE CEC 2017 benchmark function specifications. by Kankan Tang (21474968)

    Published 2025
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  11. 71
    IEEE CEC 2022 benchmark function specifications.

    IEEE CEC 2022 benchmark function specifications. by Kankan Tang (21474968)

    Published 2025
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  12. 72
    Details of the metaheuristic algorithms.

    Details of the metaheuristic algorithms. by Junhao Wei (6816803)

    Published 2025
    “…<div><p>Whale Optimization Algorithm (WOA) is a biologically inspired metaheuristic algorithm with a simple structure and ease of implementation. …”
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  13. 73
    Parameter settings for algorithms.

    Parameter settings for algorithms. by Junhao Wei (6816803)

    Published 2025
    “…<div><p>Whale Optimization Algorithm (WOA) is a biologically inspired metaheuristic algorithm with a simple structure and ease of implementation. …”
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  14. 74
    Comparison between MaAVOA and other algorithms in terms of the number of generation and number of function evaluations on DTLZs in case of the computational time is 30 seconds.

    Comparison between MaAVOA and other algorithms in terms of the number of generation and number of function evaluations on DTLZs in case of the computational time is 30 seconds. by Heba Askr (15572851)

    Published 2023
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  15. 75
    The parallel coordinates of non-dominated front obtained by each algorithm (used in the comparison) on DTLZ3 and DTLZ 7 or any function with 10 objectives.

    The parallel coordinates of non-dominated front obtained by each algorithm (used in the comparison) on DTLZ3 and DTLZ 7 or any function with 10 objectives. by Heba Askr (15572851)

    Published 2023
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  16. 76
    The components of an AVR system along with their transfer functions and adopted values.

    The components of an AVR system along with their transfer functions and adopted values. by Serdar Ekinci (15927455)

    Published 2024
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  17. 77
    AUC scores of anomaly detection algorithms.

    AUC scores of anomaly detection algorithms. by GaoXiang Zhao (21499525)

    Published 2025
    “…This strategy is integrated into a random forest algorithm by replacing the conventional voting method. …”
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  18. 78
    Recall scores of anomaly detection algorithms.

    Recall scores of anomaly detection algorithms. by GaoXiang Zhao (21499525)

    Published 2025
    “…This strategy is integrated into a random forest algorithm by replacing the conventional voting method. …”
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  19. 79
    Flowchart of MOSRS algorithm.

    Flowchart of MOSRS algorithm. by Vahid Goodarzimehr (21343124)

    Published 2025
    “…To test the performance, MOSRS is applied to the most challenging test functions set (CEC 2009) and 21 real and constrained world problems, being compared with a total of eleven metaheuristics: NSGA-II, NSGA-III, MOEA/D, MOPSO, MOGWO, ARMOEA, TiGE2, CCMO, ToP, and AnD. …”
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  20. 80
    Listed python codes of our algorithm with explanations (Python 3.9 recommended).

    Listed python codes of our algorithm with explanations (Python 3.9 recommended). by Takayuki Niizato (162226)

    Published 2023
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