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Showing 1 - 9 results of 9 for search '(( binary ms based optimization algorithm ) OR ( primary target class optimization algorithm ))', query time: 0.47s Refine Results
  1. 1
    One advantage of our algorithm is that it is not binary in nature.

    One advantage of our algorithm is that it is not binary in nature. by Yong Kuk Kim (13955214)

    Published 2022
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  2. 2
    Several loop patterns found in binary code.

    Several loop patterns found in binary code. by Alba Pedro-Zapater (8600382)

    Published 2020
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  3. 3
    Distributions of model parameters mirror differentially expressed ion channel genes.

    Distributions of model parameters mirror differentially expressed ion channel genes. by Daniele Linaro (227790)

    Published 2022
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  4. 4
    Sample image for illustration.

    Sample image for illustration. by Indhumathi S. (19173013)

    Published 2024
    “…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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  5. 5
    Comparison analysis of computation time.

    Comparison analysis of computation time. by Indhumathi S. (19173013)

    Published 2024
    “…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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  6. 6
    Process flow diagram of CBFD.

    Process flow diagram of CBFD. by Indhumathi S. (19173013)

    Published 2024
    “…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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  7. 7
    Precision recall curve.

    Precision recall curve. by Indhumathi S. (19173013)

    Published 2024
    “…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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  8. 8
    Quadratic polynomial in 2D image plane.

    Quadratic polynomial in 2D image plane. by Indhumathi S. (19173013)

    Published 2024
    “…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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  9. 9
    CIAHS-Data.xls

    CIAHS-Data.xls by Yingchang Li (22195585)

    Published 2025
    “…This method identifies inherent natural grouping points within the data through the Jenks optimization algorithm, maximizing between-class differences while minimizing within-class differences37. …”
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