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Showing 1 - 20 results of 40 for search '(( binary case based optimization algorithm ) OR ( single layer wolf optimization algorithm ))', query time: 0.36s 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
    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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  4. 4
    Several loop patterns found in binary code.

    Several loop patterns found in binary code. by Alba Pedro-Zapater (8600382)

    Published 2020
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  5. 5
    Comparison of optimization algorithms.

    Comparison of optimization algorithms. by Ning Ji (325849)

    Published 2024
    “…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …”
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  6. 6
    Algorithm comparison.

    Algorithm comparison. by Ning Ji (325849)

    Published 2024
    “…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …”
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  7. 7
    Process of GWO optimization.

    Process of GWO optimization. by Ning Ji (325849)

    Published 2024
    “…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …”
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  8. 8
    <i>hi</i>PRS algorithm process flow.

    <i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

    Published 2023
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  9. 9
    Random forest model performs better than support vector machine algorithms and when it primarily uses spontaneous photopic ERG of 60-s duration in humans.

    Random forest model performs better than support vector machine algorithms and when it primarily uses spontaneous photopic ERG of 60-s duration in humans. by Ramsés Noguez Imm (6658637)

    Published 2023
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  10. 10
    . Fitness curve.

    . Fitness curve. by Ning Ji (325849)

    Published 2024
    “…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …”
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  11. 11
    Partial faults features.

    Partial faults features. by Ning Ji (325849)

    Published 2024
    “…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …”
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  12. 12
    Diagram of faults identification.

    Diagram of faults identification. by Ning Ji (325849)

    Published 2024
    “…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …”
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  13. 13
    Confusion matrix.

    Confusion matrix. by Ning Ji (325849)

    Published 2024
    “…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …”
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  14. 14
    Sample group.

    Sample group. by Ning Ji (325849)

    Published 2024
    “…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …”
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  15. 15
    Data in the experiment.

    Data in the experiment. by Ning Ji (325849)

    Published 2024
    “…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …”
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  16. 16
    Diagram of attention mechanism.

    Diagram of attention mechanism. by Ning Ji (325849)

    Published 2024
    “…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …”
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  17. 17
    Accuracy curve.

    Accuracy curve. by Ning Ji (325849)

    Published 2024
    “…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …”
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  18. 18
    Structure of MLP.

    Structure of MLP. by Ning Ji (325849)

    Published 2024
    “…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …”
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  19. 19
    Fault recording signal.

    Fault recording signal. by Ning Ji (325849)

    Published 2024
    “…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …”
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  20. 20
    Ablation study.

    Ablation study. by Ning Ji (325849)

    Published 2024
    “…<div><p>In order to improve the accuracy of the transformer fault identification using nature-inspired algorithms, an identification method based on the GWO (Grey Wolf Optimizer)-optimized Dual-channel MLP (Multilayer Perceptron)-Attention is proposed. …”
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