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Showing 81 - 100 results of 15,991 for search '(((( algorithm i function ) OR ( algorithm based functions ))) OR ( algorithm python function ))', query time: 1.11s Refine Results
  1. 81
    Performance comparison of FBP variants on MIGD for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (10,10).

    Performance comparison of FBP variants on MIGD for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (10,10). by Qingyang Zhang (626047)

    Published 2021
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  2. 82
    Performance comparison of FBP variants on MIGD for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (10,10).

    Performance comparison of FBP variants on MIGD for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (10,10). by Qingyang Zhang (626047)

    Published 2021
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  3. 83
    Experiment 1b: Evaluating modularity-based consensus clustering pipelines on the algorithm design datasets as a function of the mixing parameter.

    Experiment 1b: Evaluating modularity-based consensus clustering pipelines on the algorithm design datasets as a function of the mixing parameter. by Yasamin Tabatabaee (18095491)

    Published 2025
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  4. 84
    Mean and standard deviation values of MIGD obtained by five algorithm for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (10,10).

    Mean and standard deviation values of MIGD obtained by five algorithm for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (10,10). by Qingyang Zhang (626047)

    Published 2021
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  5. 85
    Mean and standard deviation values of MSP obtained by five algorithms for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (10,10).

    Mean and standard deviation values of MSP obtained by five algorithms for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (10,10). by Qingyang Zhang (626047)

    Published 2021
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  6. 86
    Mean and standard deviation values of MSP obtained by five algorithms for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (10,20).

    Mean and standard deviation values of MSP obtained by five algorithms for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (10,20). by Qingyang Zhang (626047)

    Published 2021
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  7. 87
    Mean and standard deviation values of MHV obtained by five algorithms for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (5,20).

    Mean and standard deviation values of MHV obtained by five algorithms for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (5,20). by Qingyang Zhang (626047)

    Published 2021
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  8. 88
    Mean and standard deviation values of MHV obtained by five algorithms for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (10,10).

    Mean and standard deviation values of MHV obtained by five algorithms for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (10,10). by Qingyang Zhang (626047)

    Published 2021
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  9. 89
    Mean and standard deviation values of MHV obtained by five algorithms for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (10,20).

    Mean and standard deviation values of MHV obtained by five algorithms for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (10,20). by Qingyang Zhang (626047)

    Published 2021
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  10. 90
    Mean and standard deviation values of MSP obtained by five algorithms for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (5,20).

    Mean and standard deviation values of MSP obtained by five algorithms for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (5,20). by Qingyang Zhang (626047)

    Published 2021
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  11. 91
    Mean and standard deviation values of MIGD obtained by five algorithm for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (10,20).

    Mean and standard deviation values of MIGD obtained by five algorithm for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (10,20). by Qingyang Zhang (626047)

    Published 2021
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  12. 92
    Mean and standard deviation values of MIGD obtained by five algorithm for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (5,20).

    Mean and standard deviation values of MIGD obtained by five algorithm for (<i>n</i><sub><i>t</i></sub>, <i>τ</i><sub><i>t</i></sub>) = (5,20). by Qingyang Zhang (626047)

    Published 2021
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  13. 93
    Distribution of total lung capacity (TLC) in pulmonary function tests with discrepant interpretations between the algorithm and the clinicians.

    Distribution of total lung capacity (TLC) in pulmonary function tests with discrepant interpretations between the algorithm and the clinicians. by Yuh-Chin T. Huang (17867207)

    Published 2024
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  14. 94
    Search algorithm performance comparison.

    Search algorithm performance comparison. by Zhaohui Du (414105)

    Published 2025
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  15. 95
    The graphical outputs of the <i>ceRNAModule</i>, <i>ceRNASurvial</i>, and <i>ceRNALocation</i> functions.

    The graphical outputs of the <i>ceRNAModule</i>, <i>ceRNASurvial</i>, and <i>ceRNALocation</i> functions. by Yi-Wen Hsiao (13767916)

    Published 2022
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  16. 96
    <i>p</i>-value of the Wilcoxon test for the optimization results of IWOA and other algorithms based 8 benchmark functions <i>(p</i>> = 0.5 are in bold).

    <i>p</i>-value of the Wilcoxon test for the optimization results of IWOA and other algorithms based 8 benchmark functions <i>(p</i>> = 0.5 are in bold). by Wei Liu (20030)

    Published 2022
    “…<p><i>p</i>-value of the Wilcoxon test for the optimization results of IWOA and other algorithms based 8 benchmark functions <i>(p</i>> = 0.5 are in bold).…”
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  17. 97
    Performance of KLopt.lnorm function for finding <i>KL</i>-optimal designs.

    Performance of KLopt.lnorm function for finding <i>KL</i>-optimal designs. by Ray-Bing Chen (700703)

    Published 2020
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  18. 98
    Weighted cost results of DBA in different gridded graphs GG-I and GG-II/III as functions of resolution.

    Weighted cost results of DBA in different gridded graphs GG-I and GG-II/III as functions of resolution. by Tianjiao Wang (761650)

    Published 2024
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  19. 99
    If datasets are small and/or noisy, linear-regression-based algorithms for identifying functional groups outperform more complex versions.

    If datasets are small and/or noisy, linear-regression-based algorithms for identifying functional groups outperform more complex versions. by Yuanchen Zhao (12905580)

    Published 2024
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  20. 100
    Search-based testing (Genetic Algorithm) - Chapter 11 of the book "Software Testing Automation"

    Search-based testing (Genetic Algorithm) - Chapter 11 of the book "Software Testing Automation" by Saeed Parsa (13893726)

    Published 2022
    “…</p> <p><br></p> <p>3. Algorithm</p> <p>Below is the main body of the test data generator program:</p> <p>  </p> <p>the main body of a Python program to generate test data for Python functions.…”
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