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Showing 161 - 180 results of 7,061 for search '(( algorithm python function ) OR ((( algorithm shows function ) OR ( algorithm gpcr function ))))', query time: 0.30s Refine Results
  1. 161
    Compare algorithm parameter settings.

    Compare algorithm parameter settings. by Yuqi Xiong (12343771)

    Published 2025
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  2. 162
    Results of unimodal benchmark functions (F1–F7).

    Results of unimodal benchmark functions (F1–F7). by Xiaofeng Qu (577153)

    Published 2023
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  3. 163
    A hybrid algorithm based on improved threshold function and wavelet transform.

    A hybrid algorithm based on improved threshold function and wavelet transform. by Bingbing Li (461702)

    Published 2024
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  4. 164
    Comparison algorithm control parameters.

    Comparison algorithm control parameters. by Yong Gao (29929)

    Published 2023
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  5. 165
    3D modeling qualities of the AS single-template models built by including DOPE in the objective function of MODELLER.

    3D modeling qualities of the AS single-template models built by including DOPE in the objective function of MODELLER. by Giacomo Janson (8138517)

    Published 2019
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  6. 166
    The SSIM for the different algorithms.

    The SSIM for the different algorithms. by Bingbing Li (461702)

    Published 2024
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  7. 167
    APSO–WOA–CNN and APSO–CNN algorithms’ loss function validation sets.

    APSO–WOA–CNN and APSO–CNN algorithms’ loss function validation sets. by Ahmed Bahaa (12887063)

    Published 2022
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  8. 168
    APSO–WOA–CNN and APSO–CNN algorithms’ loss function training sets.

    APSO–WOA–CNN and APSO–CNN algorithms’ loss function training sets. by Ahmed Bahaa (12887063)

    Published 2022
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  9. 169
    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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  10. 170
    Comparison of functions.

    Comparison of functions. by Shufen Niu (4423717)

    Published 2023
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  11. 171
    Results of test functions (F12–15) with fixed dimensions.

    Results of test functions (F12–15) with fixed dimensions. by Dingming Yang (8505990)

    Published 2022
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  12. 172
    Composite benchmark functions.

    Composite benchmark functions. by Qi Song (121209)

    Published 2021
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  13. 173
    Unimodal benchmark functions.

    Unimodal benchmark functions. by Qi Song (121209)

    Published 2021
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  14. 174
    3D modeling qualities of the AM multiple-template models built by including DOPE in the objective function of MODELLER.

    3D modeling qualities of the AM multiple-template models built by including DOPE in the objective function of MODELLER. by Giacomo Janson (8138517)

    Published 2019
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  15. 175
    EALM algorithm.

    EALM algorithm. by Weibo Wang (782424)

    Published 2022
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  16. 176
    Route for bays29 output by ABSQL algorithm.

    Route for bays29 output by ABSQL algorithm. by Jin Zhang (53297)

    Published 2023
    “…The experimental results show that DSRABSQL significantly outperforms the other algorithms. …”
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  17. 177
    Simulation parameters for the QL, ABSQL and DSRABSQL algorithms.

    Simulation parameters for the QL, ABSQL and DSRABSQL algorithms. by Jin Zhang (53297)

    Published 2023
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  18. 178
    Ave and Std of different algorithms.

    Ave and Std of different algorithms. by Yanzhao Gu (21192659)

    Published 2025
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  19. 179
    Parameter settings for metaheuristic algorithm.

    Parameter settings for metaheuristic algorithm. by Yanzhao Gu (21192659)

    Published 2025
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  20. 180
    Scheduling time of five algorithms.

    Scheduling time of five algorithms. by Huichao Guo (14515171)

    Published 2025
    “…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …”
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