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driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
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Showing 1 - 20 results of 42 for search '(( binary based driven optimization algorithm ) OR ( binary data field optimization algorithm ))', query time: 0.52s Refine Results
  1. 1
    Binary contingency table.

    Binary contingency table. by Lu Xiao (314030)

    Published 2024
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  2. 2
    Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things

    Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things by Ashok Kumar K (21441108)

    Published 2025
    “…Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …”
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  3. 3
    Parameter settings of the comparison algorithms.

    Parameter settings of the comparison algorithms. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  4. 4
    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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  5. 5
    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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  6. 6
    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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  7. 7
    Datasets and their properties.

    Datasets and their properties. by Olaide N. Oyelade (14047002)

    Published 2023
    “…<div><p>Feature selection problem represents the field of study that requires approximate algorithms to identify discriminative and optimally combined features. …”
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  8. 8
    Parameter settings.

    Parameter settings. by Olaide N. Oyelade (14047002)

    Published 2023
    “…<div><p>Feature selection problem represents the field of study that requires approximate algorithms to identify discriminative and optimally combined features. …”
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  9. 9
    the functioning of BRPSO.

    the functioning of BRPSO. by Hossein Jarrahi (22530251)

    Published 2025
    “…A sensitivity analysis of key RFD parameters, including frictional moment and rigid beam length, highlights their influence on seismic performance. The optimization problem is formulated based on the seismic energy dissipation concept, employing a modified binary and real-coded particle swarm optimization (BRPSO) algorithm. …”
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  10. 10
    Characteristic of 6- and 10-story SMRF [99,98].

    Characteristic of 6- and 10-story SMRF [99,98]. by Hossein Jarrahi (22530251)

    Published 2025
    “…A sensitivity analysis of key RFD parameters, including frictional moment and rigid beam length, highlights their influence on seismic performance. The optimization problem is formulated based on the seismic energy dissipation concept, employing a modified binary and real-coded particle swarm optimization (BRPSO) algorithm. …”
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  11. 11
    The RFD’s behavior mechanism (2002).

    The RFD’s behavior mechanism (2002). by Hossein Jarrahi (22530251)

    Published 2025
    “…A sensitivity analysis of key RFD parameters, including frictional moment and rigid beam length, highlights their influence on seismic performance. The optimization problem is formulated based on the seismic energy dissipation concept, employing a modified binary and real-coded particle swarm optimization (BRPSO) algorithm. …”
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  12. 12
    Data_Sheet_1_Crystal Structure Prediction of Binary Alloys via Deep Potential.PDF

    Data_Sheet_1_Crystal Structure Prediction of Binary Alloys via Deep Potential.PDF by Haidi Wang (9694004)

    Published 2020
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  13. 13
    Schematic representation of semi-automated algorithm for organoids analyzing.

    Schematic representation of semi-automated algorithm for organoids analyzing. by Anna Demchenko (18449439)

    Published 2025
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  14. 14
    Comparison in terms of the sensitivity.

    Comparison in terms of the sensitivity. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  15. 15
    Parameter sensitivity of BIMGO.

    Parameter sensitivity of BIMGO. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  16. 16
    Details of the medical datasets.

    Details of the medical datasets. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  17. 17
    The flowchart of IMGO.

    The flowchart of IMGO. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  18. 18
    Comparison in terms of the selected features.

    Comparison in terms of the selected features. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  19. 19
    Iterative chart of control factor.

    Iterative chart of control factor. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  20. 20
    Details of 23 basic benchmark functions.

    Details of 23 basic benchmark functions. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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