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Showing 121 - 140 results of 5,085 for search '(((( algorithm b function ) OR ( algorithm pre functions ))) OR ( algorithm python function ))', query time: 0.69s Refine Results
  1. 121
    Sets of best performing parameters obtained after gridsearching through different values for each classification algorithm.

    Sets of best performing parameters obtained after gridsearching through different values for each classification algorithm. by Adhiraj Nath (17118269)

    Published 2023
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  2. 122
    Schematic diagram of the TEAPS algorithm.

    Schematic diagram of the TEAPS algorithm. by Yoshiaki Kariya (13767985)

    Published 2022
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  3. 123
    Gene function enrichment analysis: GO function enrichment analysis (A) and KEGG pathway enrichment analysis (B).

    Gene function enrichment analysis: GO function enrichment analysis (A) and KEGG pathway enrichment analysis (B). by Yaling Hu (11648397)

    Published 2021
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  4. 124
    Flowchart of the phase optimization algorithm.

    Flowchart of the phase optimization algorithm. by Maxim Terekhov (3429614)

    Published 2021
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  5. 125
    HIV exposure risk algorithm. HIV exposure risk algorithm based on available data from the Tonse Padmozi trial.

    HIV exposure risk algorithm. HIV exposure risk algorithm based on available data from the Tonse Padmozi trial. by Anna M. Leone (22486372)

    Published 2025
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  6. 126
    CPU runtime of each algorithm: (a) Running Time Comparison of Different Algorithms on F1-F10 and (b) Running Time Comparison of Different Algorithms on F11-F20.

    CPU runtime of each algorithm: (a) Running Time Comparison of Different Algorithms on F1-F10 and (b) Running Time Comparison of Different Algorithms on F11-F20. by Ruyi Dong (9038174)

    Published 2025
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  7. 127
    <b>The Application of the Optimized Genetic Algorithm in SerDes Circuit Design</b>

    <b>The Application of the Optimized Genetic Algorithm in SerDes Circuit Design</b> by Xuan Wei (18564826)

    Published 2024
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  8. 128
    Comparison of scores obtained by our interpenetration and scoring algorithm (ISA) and ROSETTA for a subset of structures.

    Comparison of scores obtained by our interpenetration and scoring algorithm (ISA) and ROSETTA for a subset of structures. by Kevin Sawade (16726527)

    Published 2023
    “…Our ISA algorithm correlates with the much more sophisticated ROSETTA algorithm with a Pearson correlation coefficient of 0.88 (B). …”
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  9. 129
    Tunable parameters in stimuli generation module. <sup><i>a</i></sup>The fixation cross is displayed once before an experiment starts to help subjects concentrate. <sup><i>b</i></sup>Different stimuli are displayed equally. If desired by the user, some stimuli can be displayed more/less frequently by assigning them a higher/lower weight.

    Tunable parameters in stimuli generation module. <sup><i>a</i></sup>The fixation cross is displayed once before an experiment starts to help subjects concentrate. <sup><i>b</i></su... by Gursimran Singh (575288)

    Published 2025
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  10. 130
    Proposed algorithm flowchart.

    Proposed algorithm flowchart. by Fadhil Mukhlif (8411451)

    Published 2020
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  11. 131
    Modeling with uniform <i>σ</i> values.

    Modeling with uniform <i>σ</i> values. by Giacomo Janson (8138517)

    Published 2019
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  12. 132
    Iteration curve of each algorithm: (a) Convergence curves of the average best fitness for functions F1-F10, (b) Convergence curves of the average best fitness for functions F11-F20 and (c) Correspondence between curve colors and algorithms.

    Iteration curve of each algorithm: (a) Convergence curves of the average best fitness for functions F1-F10, (b) Convergence curves of the average best fitness for functions F11-F20 and (c) Correspondence between curve colors and algorithms. by Ruyi Dong (9038174)

    Published 2025
    “…<p>Iteration curve of each algorithm: (a) Convergence curves of the average best fitness for functions F1-F10, (b) Convergence curves of the average best fitness for functions F11-F20 and (c) Correspondence between curve colors and algorithms.…”
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  13. 133
    Effect of <i>|Δd</i><sub><i>n</i></sub><i>|</i> perturbation on 3D modeling.

    Effect of <i>|Δd</i><sub><i>n</i></sub><i>|</i> perturbation on 3D modeling. by Giacomo Janson (8138517)

    Published 2019
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  14. 134
    Performance comparison in CP-EE model (a) SVR model (b) BPNN model (c) RF model (d) MS-GEP model.

    Performance comparison in CP-EE model (a) SVR model (b) BPNN model (c) RF model (d) MS-GEP model. by Jin Ding (11522)

    Published 2023
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  15. 135
    Convergence curve of others functions compared with the PSO family algorithms.

    Convergence curve of others functions compared with the PSO family algorithms. by Yong Gao (29929)

    Published 2023
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  16. 136
    Convergence curve of unimodal functions compared with the PSO family algorithms.

    Convergence curve of unimodal functions compared with the PSO family algorithms. by Yong Gao (29929)

    Published 2023
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  17. 137
    Convergence curve of unimodal functions compared with the meta-heuristic algorithms.

    Convergence curve of unimodal functions compared with the meta-heuristic algorithms. by Yong Gao (29929)

    Published 2023
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  18. 138
    Convergence curve of others functions compared with the meta-heuristic algorithms.

    Convergence curve of others functions compared with the meta-heuristic algorithms. by Yong Gao (29929)

    Published 2023
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  19. 139
    Convergence curve of multimodal functions compared with the meta-heuristic algorithms.

    Convergence curve of multimodal functions compared with the meta-heuristic algorithms. by Yong Gao (29929)

    Published 2023
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  20. 140
    Convergence curve of multimodal functions compared with the PSO family algorithms.

    Convergence curve of multimodal functions compared with the PSO family algorithms. by Yong Gao (29929)

    Published 2023
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