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Showing 1 - 20 results of 37 for search '(( algorithm harding function ) OR ( algorithm spc function ))', query time: 0.46s Refine Results
  1. 1
    Summary of greedy algorithms presented in this section. Details of approximation factors for FastGreedy and UnitGreedy may be found in [26] and [25], respectively.

    Summary of greedy algorithms presented in this section. Details of approximation factors for FastGreedy and UnitGreedy may be found in [26] and [25], respectively. by Jeffrey Keithley (14626551)

    Published 2025
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  2. 2
    Percentage totBurden and percentage maxBurden reduced by UnitGreedy, SingletonGreedy, FastGreedy and baselines for = 0.535 in Iowa for FRED (first column) and SafeGraph (second column).

    Percentage totBurden and percentage maxBurden reduced by UnitGreedy, SingletonGreedy, FastGreedy and baselines for = 0.535 in Iowa for FRED (first column) and SafeGraph (second col... by Jeffrey Keithley (14626551)

    Published 2025
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  3. 3
    Metapopulation model notation.

    Metapopulation model notation. by Jeffrey Keithley (14626551)

    Published 2025
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  4. 4
    Estimates of for each problem instance.

    Estimates of for each problem instance. by Jeffrey Keithley (14626551)

    Published 2025
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  5. 5
    The instance of MaxCasesAverted and MaxPeaksReduced is a graph <i>G</i> constructed from the given instance of Max k-SI.

    The instance of MaxCasesAverted and MaxPeaksReduced is a graph <i>G</i> constructed from the given instance of Max k-SI. by Jeffrey Keithley (14626551)

    Published 2025
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  6. 6
    Percentage totBurden and percentage maxBurden reduced by UnitGreedy, FastGreedy and baselines for = 0.525 in Texas for FRED (first column) and SafeGraph (second column).

    Percentage totBurden and percentage maxBurden reduced by UnitGreedy, FastGreedy and baselines for = 0.525 in Texas for FRED (first column) and SafeGraph (second column). by Jeffrey Keithley (14626551)

    Published 2025
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  7. 7
    Approximation factors for each problem instance.

    Approximation factors for each problem instance. by Jeffrey Keithley (14626551)

    Published 2025
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  8. 8
    Percentage totBurden and percentage maxBurden reduced by all approaches for = 0.5345 in New Hampshire for FRED (first column) and SafeGraph (second column).

    Percentage totBurden and percentage maxBurden reduced by all approaches for = 0.5345 in New Hampshire for FRED (first column) and SafeGraph (second column). by Jeffrey Keithley (14626551)

    Published 2025
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  9. 9
    FastGreedy, UnitGreedy, SingletonGreedy, 3-EnumGreedy, and POMS comparison with respect to practical running time (estimated for POMS) to achieve approximation guarantee for New Hampshire with and budgets.

    FastGreedy, UnitGreedy, SingletonGreedy, 3-EnumGreedy, and POMS comparison with respect to practical running time (estimated for POMS) to achieve approximation guarantee for New Ha... by Jeffrey Keithley (14626551)

    Published 2025
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  10. 10
    The parameters of algorithms.

    The parameters of algorithms. by Le Huu Binh (18340233)

    Published 2025
    “…However, solving the RNP problem in WMN is difficult because it is NP-hard. As a result, this problem can only be solved using approximate optimization algorithms such as heuristics and meta-heuristics. …”
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  11. 11
    Optimization process of fitness function .

    Optimization process of fitness function . by Yuehong Zhang (82779)

    Published 2025
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  12. 12
    Cost function calculated by QA with different hyperparameters.

    Cost function calculated by QA with different hyperparameters. by Takuro Matsuta (21608505)

    Published 2025
    Subjects: “…currently available algorithms…”
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  13. 13
    Cost function calculated by SA with different hyperparameters.

    Cost function calculated by SA with different hyperparameters. by Takuro Matsuta (21608505)

    Published 2025
    Subjects: “…currently available algorithms…”
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  14. 14
    Objective functions and solving methods for PVRP problems with time windows, multiple depots, and a heterogeneous fleet.

    Objective functions and solving methods for PVRP problems with time windows, multiple depots, and a heterogeneous fleet. by Alejandro Arenas-Vasco (19797133)

    Published 2024
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  15. 15
    ddPCR mtDNA amplicon concentration as a function of distance.

    ddPCR mtDNA amplicon concentration as a function of distance. by Patrick Kurtz (21772385)

    Published 2025
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  16. 16
    Using synthetic data to test group-searching algorithms in a context where the correct grouping of species is known and uniquely defined.

    Using synthetic data to test group-searching algorithms in a context where the correct grouping of species is known and uniquely defined. by Yuanchen Zhao (12905580)

    Published 2024
    “…The reaction network is assumed to form a linear degradation chain 1 → 2 → ⋯ → <i>N</i> with the end-product concentration (metabolite <i>N</i>, orange) taken as the function of interest (shown with <i>N</i> = 3 as an example). …”
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  17. 17
    Streamfunction calculated by QA with different with different grid resolutions Streamfunction averaged over 10 runs from QA (shading) and the “true” solution (black contour lines) for

    Streamfunction calculated by QA with different with different grid resolutions Streamfunction averaged over 10 runs from QA (shading) and the “true” solution (black contour lines)... by Takuro Matsuta (21608505)

    Published 2025
    Subjects: “…currently available algorithms…”
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  18. 18
    QA and SA solutions by truncated spectral expansion when

    QA and SA solutions by truncated spectral expansion when by Takuro Matsuta (21608505)

    Published 2025
    Subjects: “…currently available algorithms…”
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  19. 19
    Streamfunction calculated by SA with different hyperparameters.

    Streamfunction calculated by SA with different hyperparameters. by Takuro Matsuta (21608505)

    Published 2025
    Subjects: “…currently available algorithms…”
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  20. 20
    QA and SA solutions by truncated spectral expansion when

    QA and SA solutions by truncated spectral expansion when by Takuro Matsuta (21608505)

    Published 2025
    Subjects: “…currently available algorithms…”
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