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Showing 1 - 20 results of 89 for search '(( binary task guided optimization algorithm ) OR ( primary data design optimization algorithm ))*', query time: 0.57s Refine Results
  1. 1
    Optimal results of the different algorithms on the speed design reducer problem.

    Optimal results of the different algorithms on the speed design reducer problem. by Guangwei Liu (181992)

    Published 2023
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  2. 2
    Optimal results of the different algorithms on the pressure vessel design problem.

    Optimal results of the different algorithms on the pressure vessel design problem. by Guangwei Liu (181992)

    Published 2023
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  3. 3
    Optimal results of the different algorithms on the gear train design problem.

    Optimal results of the different algorithms on the gear train design problem. by Guangwei Liu (181992)

    Published 2023
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  4. 4
    Optimal results of the different algorithms on the tension/compression spring design problem.

    Optimal results of the different algorithms on the tension/compression spring design problem. by Guangwei Liu (181992)

    Published 2023
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  5. 5
    Layout of the primary 3D manufacturing cell facility [5].

    Layout of the primary 3D manufacturing cell facility [5]. by Yanlin Zhao (251552)

    Published 2024
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  6. 6
    Principle of the SVM algorithm.

    Principle of the SVM algorithm. by Anfeng Zhu (17817144)

    Published 2024
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  7. 7
    Speed reducer design problem.

    Speed reducer design problem. by Guangwei Liu (181992)

    Published 2023
    “…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …”
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  8. 8
    Pressure vessel design problem.

    Pressure vessel design problem. by Guangwei Liu (181992)

    Published 2023
    “…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …”
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  9. 9
    Gear train design problem.

    Gear train design problem. by Guangwei Liu (181992)

    Published 2023
    “…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …”
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  10. 10
    Tension/compression spring design problem.

    Tension/compression spring design problem. by Guangwei Liu (181992)

    Published 2023
    “…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …”
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  11. 11
    The Pseudo-Code of the IRBMO Algorithm.

    The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

    Published 2025
    “…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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  12. 12
    Zimbabwe model outputs on actual and optimized 2016 spending and impact by intervention.

    Zimbabwe model outputs on actual and optimized 2016 spending and impact by intervention. by Nicole Fraser-Hurt (2636833)

    Published 2021
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  13. 13
    IRBMO vs. meta-heuristic algorithms boxplot.

    IRBMO vs. meta-heuristic algorithms boxplot. by Chenyi Zhu (9383370)

    Published 2025
    “…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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  14. 14
    IRBMO vs. feature selection algorithm boxplot.

    IRBMO vs. feature selection algorithm boxplot. by Chenyi Zhu (9383370)

    Published 2025
    “…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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  15. 15
    Côte d’Ivoire model outputs on actual and optimized 2016 spending and impact by care delivery platform.

    Côte d’Ivoire model outputs on actual and optimized 2016 spending and impact by care delivery platform. by Nicole Fraser-Hurt (2636833)

    Published 2021
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  16. 16
    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology

    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

    Published 2024
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  17. 17
    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology

    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

    Published 2024
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  18. 18
    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology

    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

    Published 2024
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  19. 19
    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology

    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

    Published 2024
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  20. 20
    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology

    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

    Published 2024
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