يعرض 1 - 20 نتائج من 32 نتيجة بحث عن '(( binary more design optimization algorithm ) OR ( binary climate wolf optimization algorithm ))', وقت الاستعلام: 0.51s تنقيح النتائج
  1. 1

    MSE for ILSTM algorithm in binary classification. حسب Asmaa Ahmed Awad (16726315)

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
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  3. 3

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

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"
  4. 4

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

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"
  5. 5

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

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"
  6. 6

    Triplet Matching for Estimating Causal Effects With Three Treatment Arms: A Comparative Study of Mortality by Trauma Center Level حسب Giovanni Nattino (561797)

    منشور في 2021
    "…Few studies, however, have used matching designs with more than two groups, due to the complexity of matching algorithms. …"
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    Pseudo Code of RBMO. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"
  8. 8

    P-value on CEC-2017(Dim = 30). حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"
  9. 9

    Memory storage behavior. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"
  10. 10

    Elite search behavior. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"
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    Description of the datasets. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"
  12. 12

    S and V shaped transfer functions. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"
  13. 13

    S- and V-Type transfer function diagrams. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"
  14. 14

    Collaborative hunting behavior. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"
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    Friedman average rank sum test results. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"
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    IRBMO vs. variant comparison adaptation data. حسب Chenyi Zhu (9383370)

    منشور في 2025
    "…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"
  17. 17

    Multicategory Angle-Based Learning for Estimating Optimal Dynamic Treatment Regimes With Censored Data حسب Fei Xue (24567)

    منشور في 2021
    "…Specifically, the proposed method obtains the optimal DTR via integrating estimations of decision rules at multiple stages into a single multicategory classification algorithm without imposing additional constraints, which is also more computationally efficient and robust. …"
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    Summary of LITNET-2020 dataset. حسب Asmaa Ahmed Awad (16726315)

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
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    SHAP analysis for LITNET-2020 dataset. حسب Asmaa Ahmed Awad (16726315)

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
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    Comparison of intrusion detection systems. حسب Asmaa Ahmed Awad (16726315)

    منشور في 2023
    "…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"