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phase optimization » whale optimization (Expand Search), based optimization (Expand Search), path optimization (Expand Search)
work optimization » wolf optimization (Expand Search), swarm optimization (Expand Search), dose optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
lines based » lens based (Expand Search), genes based (Expand Search), lines used (Expand Search)
based phase » based case (Expand Search)
based work » based network (Expand Search)
Showing 1 - 20 results of 106 for search '(( lines based work optimization algorithm ) OR ( binary based phase optimization algorithm ))*', query time: 0.79s Refine Results
  1. 1
    Comparison between ILSTM and machine learning-based algorithms in binary classification.

    Comparison between ILSTM and machine learning-based algorithms in binary classification. by Asmaa Ahmed Awad (16726315)

    Published 2023
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  2. 2
    Comparison between ILSTM and deep learning-based algorithms in binary classification.

    Comparison between ILSTM and deep learning-based algorithms in binary classification. by Asmaa Ahmed Awad (16726315)

    Published 2023
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  3. 3
    The flowchart showing the optimization process of the hybrid methods using BEOSA as the base algorithm and SA and FFA as integrated algorithms.

    The flowchart showing the optimization process of the hybrid methods using BEOSA as the base algorithm and SA and FFA as integrated algorithms. by Olaide N. Oyelade (14047002)

    Published 2023
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  4. 4
    MSE for ILSTM algorithm in binary classification.

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

    Published 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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  5. 5
    DataSheet1_Multi-Objective Optimization Design of Ladle Refractory Lining Based on Genetic Algorithm.docx

    DataSheet1_Multi-Objective Optimization Design of Ladle Refractory Lining Based on Genetic Algorithm.docx by Ying Sun (23237)

    Published 2022
    “…In this paper, a genetic algorithm-based optimization method for ladle refractory lining structure is proposed. …”
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  6. 6
    DMTD algorithm.

    DMTD algorithm. by Yunhu Huang (21402795)

    Published 2025
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  7. 7
    Working condition arrangement.

    Working condition arrangement. by Jian Yang (12136)

    Published 2024
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  8. 8
    Comparison of performance with complex continuous lines.

    Comparison of performance with complex continuous lines. by Yunhu Huang (21402795)

    Published 2025
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  9. 9
    Operation curve comparison among the EITO algorithms.

    Operation curve comparison among the EITO algorithms. by Yunhu Huang (21402795)

    Published 2025
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  10. 10
    Operation curve comparison among the EITO algorithms.

    Operation curve comparison among the EITO algorithms. by Yunhu Huang (21402795)

    Published 2025
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  11. 11
    Operation curve comparison among the five algorithms in the 95 s trip.

    Operation curve comparison among the five algorithms in the 95 s trip. by Yunhu Huang (21402795)

    Published 2025
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  12. 12
    Operation curve comparison among the five algorithms in the 115 s trip.

    Operation curve comparison among the five algorithms in the 115 s trip. by Yunhu Huang (21402795)

    Published 2025
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  13. 13
    Operation curve comparison among the five algorithms in the 101s trip.

    Operation curve comparison among the five algorithms in the 101s trip. by Yunhu Huang (21402795)

    Published 2025
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  14. 14
    Flowchart of the proposed work.

    Flowchart of the proposed work. by Weifeng Liu (635311)

    Published 2024
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  15. 15
    Linear-regression-based algorithms succeed at identifying the correct functional groups in synthetic data, and multi-group algorithms recover more information.

    Linear-regression-based algorithms succeed at identifying the correct functional groups in synthetic data, and multi-group algorithms recover more information. by Yuanchen Zhao (12905580)

    Published 2024
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  16. 16
    EITO<sub>P</sub> with flexible trip time.

    EITO<sub>P</sub> with flexible trip time. by Yunhu Huang (21402795)

    Published 2025
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  17. 17
    Energy consumption in the PPO process.

    Energy consumption in the PPO process. by Yunhu Huang (21402795)

    Published 2025
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  18. 18
    Speed limits.

    Speed limits. by Yunhu Huang (21402795)

    Published 2025
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  19. 19
    Running time in the PPO process.

    Running time in the PPO process. by Yunhu Huang (21402795)

    Published 2025
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  20. 20
    Speed limits and gradients from RJ to WYJ.

    Speed limits and gradients from RJ to WYJ. by Yunhu Huang (21402795)

    Published 2025
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