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Showing 1 - 20 results of 6,809 for search '(((( algorithm design function ) OR ( algorithm time function ))) OR ( algorithm python function ))', query time: 0.65s Refine Results
  1. 1
    Modular architecture design of PyNoetic showing all its constituent functions.

    Modular architecture design of PyNoetic showing all its constituent functions. by Gursimran Singh (575288)

    Published 2025
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  2. 2
    Results of searching performance of the improved NAG algorithm on Rosenbrock function, Ackley function, and Rastrigin function.

    Results of searching performance of the improved NAG algorithm on Rosenbrock function, Ackley function, and Rastrigin function. by Rui Zhang (13940)

    Published 2021
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  3. 3
    Results of searching performance of different algorithm models on the Rosenbrock function, Ackley function, and Rastrigin function.

    Results of searching performance of different algorithm models on the Rosenbrock function, Ackley function, and Rastrigin function. by Rui Zhang (13940)

    Published 2021
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  4. 4
    Results of searching performance of different algorithm models on the Sphere function and Griewank function.

    Results of searching performance of different algorithm models on the Sphere function and Griewank function. by Rui Zhang (13940)

    Published 2021
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  5. 5
    Results of searching performance of the improved NAG algorithm on Sphere function and Griewank function.

    Results of searching performance of the improved NAG algorithm on Sphere function and Griewank function. by Rui Zhang (13940)

    Published 2021
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  6. 6
    Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks.

    Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. by Gursimran Singh (575288)

    Published 2025
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  7. 7
    <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
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  8. 8
    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
    “…In `main.py`, the parameters for the TAMS algorithm are specified (trajectory time, time step, score function, number of particles, type of score threshold, maximum number of iterations, noise level etc.). …”
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  9. 9
    Function graph and algorithm iterative graph.

    Function graph and algorithm iterative graph. by WanRu Zhao (18980374)

    Published 2024
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  10. 10
    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
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  11. 11
    Run times of two algorithms.

    Run times of two algorithms. by Gourab Saha (8987405)

    Published 2025
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  12. 12
    Code snippets to add user-specific custom functionality in PyNoetic.

    Code snippets to add user-specific custom functionality in PyNoetic. by Gursimran Singh (575288)

    Published 2025
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  13. 13
    Details of path flows and path travel times by the proposed algorithms.

    Details of path flows and path travel times by the proposed algorithms. by C. K. Wong (3224922)

    Published 2019
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  14. 14
    Performance comparison of recent and effective algorithms for minimizing error-based cost functions.

    Performance comparison of recent and effective algorithms for minimizing error-based cost functions. by Davut Izci (15927452)

    Published 2023
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  15. 15
    Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results

    Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

    Published 2025
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  16. 16
    Objective functions (i.e., RMSEs) and time of optimization for different population sizes of the used algorithms.

    Objective functions (i.e., RMSEs) and time of optimization for different population sizes of the used algorithms. by Yao Peng (1928524)

    Published 2023
    “…<p>Objective functions (i.e., RMSEs) and time of optimization for different population sizes of the used algorithms.…”
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  17. 17
    Boxplots obtained by testing rat575 for 20 times by each algorithm.

    Boxplots obtained by testing rat575 for 20 times by each algorithm. by Jin Zhang (53297)

    Published 2023
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  18. 18
    Boxplots obtained by testing ch150 for 50 times by each algorithm.

    Boxplots obtained by testing ch150 for 50 times by each algorithm. by Jin Zhang (53297)

    Published 2023
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  19. 19
    Boxplots obtained by testing fl1400 for 10 times by each algorithm.

    Boxplots obtained by testing fl1400 for 10 times by each algorithm. by Jin Zhang (53297)

    Published 2023
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  20. 20
    Comparative statistical performance of various algorithms in minimizing the <i>F</i> cost function.

    Comparative statistical performance of various algorithms in minimizing the <i>F</i> cost function. by Davut Izci (15927452)

    Published 2023
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