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required optimization » guided optimization (Expand Search), resource optimization (Expand Search), feature optimization (Expand Search)
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Showing 121 - 140 results of 259 for search '(( binary task required optimization algorithm ) OR ( less based process optimization algorithm ))', query time: 1.06s Refine Results
  1. 121
    The bottleneck residual block for Resnet50.

    The bottleneck residual block for Resnet50. by Nour Eldeen Mahmoud Khalifa (19259450)

    Published 2024
    “…</p><p>Method</p><p>In this paper, a deep fusion model based on whale optimization and an artificial neural network for Arabian date classification is proposed. …”
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  2. 122
    DeepDate model’s architecture design.

    DeepDate model’s architecture design. by Nour Eldeen Mahmoud Khalifa (19259450)

    Published 2024
    “…</p><p>Method</p><p>In this paper, a deep fusion model based on whale optimization and an artificial neural network for Arabian date classification is proposed. …”
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  3. 123
    Video_1_Simulating human walking: a model-based reinforcement learning approach with musculoskeletal modeling.MP4

    Video_1_Simulating human walking: a model-based reinforcement learning approach with musculoskeletal modeling.MP4 by Binbin Su (640741)

    Published 2023
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  4. 124
    Pmd analysis of the SST-CRN model with several CR users.

    Pmd analysis of the SST-CRN model with several CR users. by Saraswathi M. (19353597)

    Published 2024
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  5. 125
    Probability of detection analysis of SST-CRN model under non-fading channels.

    Probability of detection analysis of SST-CRN model under non-fading channels. by Saraswathi M. (19353597)

    Published 2024
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  6. 126
    A summary of related work in CRN.

    A summary of related work in CRN. by Saraswathi M. (19353597)

    Published 2024
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  7. 127
    Analysis of SST-CRN model results for spectral hole exploitation probability.

    Analysis of SST-CRN model results for spectral hole exploitation probability. by Saraswathi M. (19353597)

    Published 2024
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  8. 128
    Illustration for the SST-CRN model.

    Illustration for the SST-CRN model. by Saraswathi M. (19353597)

    Published 2024
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  9. 129
    Pe investigation of the SST-CRN under fading channels.

    Pe investigation of the SST-CRN under fading channels. by Saraswathi M. (19353597)

    Published 2024
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  10. 130
    Pnf analysis of the SST-CRN model.

    Pnf analysis of the SST-CRN model. by Saraswathi M. (19353597)

    Published 2024
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  11. 131
    Flowchart of CSA.

    Flowchart of CSA. by Saraswathi M. (19353597)

    Published 2024
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  12. 132
    Pe analysis of the SST-CRN model under non-fading channels.

    Pe analysis of the SST-CRN model under non-fading channels. by Saraswathi M. (19353597)

    Published 2024
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  13. 133
    Probability of detection analysis of SST-CRN model under fading channels.

    Probability of detection analysis of SST-CRN model under fading channels. by Saraswathi M. (19353597)

    Published 2024
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  14. 134
    Pd analysis of the SST-CRN model under fading channels.

    Pd analysis of the SST-CRN model under fading channels. by Saraswathi M. (19353597)

    Published 2024
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  15. 135
    Probability of error analysis of SST-CRN under fading channels.

    Probability of error analysis of SST-CRN under fading channels. by Saraswathi M. (19353597)

    Published 2024
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  16. 136
    Pmd analysis of the SST-CRN model.

    Pmd analysis of the SST-CRN model. by Saraswathi M. (19353597)

    Published 2024
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  17. 137
    Pd analysis of the SST-CRN model under non-fading channels.

    Pd analysis of the SST-CRN model under non-fading channels. by Saraswathi M. (19353597)

    Published 2024
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  18. 138
    Structure of DBN model.

    Structure of DBN model. by Saraswathi M. (19353597)

    Published 2024
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  19. 139
    Probability of error analysis of SST-CRN model under non-fading channels.

    Probability of error analysis of SST-CRN model under non-fading channels. by Saraswathi M. (19353597)

    Published 2024
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  20. 140
    GA process.

    GA process. by Jianpeng Zhang (528185)

    Published 2025
    “…GA is used to optimize the feature selection process to identify the key feature subsets that have the greatest impact on model performance. …”
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