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Showing 1 - 20 results of 1,491 for search '(((( complex functions algorithm ) OR ( element te algorithm ))) OR ( neural coding algorithm ))', query time: 0.55s Refine Results
  1. 1
    Dataset for Fine-Tuning Code Generation Models: Kannada-English Algorithmic Statements and Python Code

    Dataset for Fine-Tuning Code Generation Models: Kannada-English Algorithmic Statements and Python Code by Goutami Sooda (20714729)

    Published 2025
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  2. 2
    Results obtained by different algorithms on 23 benchmark functions.

    Results obtained by different algorithms on 23 benchmark functions. by Yuqi Xiong (12343771)

    Published 2025
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  3. 3
    Convergence curves obtained by different algorithms on 23 benchmark functions.

    Convergence curves obtained by different algorithms on 23 benchmark functions. by Yuqi Xiong (12343771)

    Published 2025
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  4. 4
    Different algorithms in 23 benchmark functions to obtain partial boxplot.

    Different algorithms in 23 benchmark functions to obtain partial boxplot. by Yuqi Xiong (12343771)

    Published 2025
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  5. 5
    Results obtained by different algorithms on CEC2022 benchmark functions.

    Results obtained by different algorithms on CEC2022 benchmark functions. by Yuqi Xiong (12343771)

    Published 2025
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  6. 6
    Data and code resources.

    Data and code resources. by Sam Hall-McMaster (10343795)

    Published 2025
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  7. 7
    Convergence curves obtained by different algorithms on CEC2022 benchmark functions.

    Convergence curves obtained by different algorithms on CEC2022 benchmark functions. by Yuqi Xiong (12343771)

    Published 2025
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  8. 8
    Multimodal test functions.

    Multimodal test functions. by HaoCheng Wang (6089567)

    Published 2025
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  9. 9
    Unimodal test functions.

    Unimodal test functions. by HaoCheng Wang (6089567)

    Published 2025
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  10. 10
    Fixed multimodal test functions.

    Fixed multimodal test functions. by HaoCheng Wang (6089567)

    Published 2025
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  11. 11
    Convergence curves of various algorithms under test functions.

    Convergence curves of various algorithms under test functions. by Jiayuan Wang (3765376)

    Published 2025
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  12. 12
    Convergence curves of various algorithms under test functions.

    Convergence curves of various algorithms under test functions. by Jiayuan Wang (3765376)

    Published 2025
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  13. 13
    The effect of each parameter on the target functions.

    The effect of each parameter on the target functions. by Shangyang Jin (21772466)

    Published 2025
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  14. 14
    Functional fitness test results of different algorithms.

    Functional fitness test results of different algorithms. by Ling Zhao (111365)

    Published 2025
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  15. 15
    TIR-Learner v3: New generation TE annotation program for identifying TIRs

    TIR-Learner v3: New generation TE annotation program for identifying TIRs by Tianyu Lu (18856792)

    Published 2025
    “…The old TIR suffers from slow execution on large genomes due to intense I/O operations and less efficient algorithms, it also lacks maintainability due to legacy dependency issues. …”
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  16. 16
    Experimental results of NAFPSO algorithm with pipeline complexity of 0.7.

    Experimental results of NAFPSO algorithm with pipeline complexity of 0.7. by Huichao Guo (14515171)

    Published 2025
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  17. 17
    Experimental results of NAFPSO algorithm with pipeline complexity of 0.5.

    Experimental results of NAFPSO algorithm with pipeline complexity of 0.5. by Huichao Guo (14515171)

    Published 2025
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  18. 18
    Experimental results of NAFPSO algorithm with pipeline complexity of 0.6.

    Experimental results of NAFPSO algorithm with pipeline complexity of 0.6. by Huichao Guo (14515171)

    Published 2025
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  19. 19
    Comparison of performance with complex continuous lines.

    Comparison of performance with complex continuous lines. by Yunhu Huang (21402795)

    Published 2025
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  20. 20
    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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