بدائل البحث:
design optimization » bayesian optimization (توسيع البحث)
guided optimization » based optimization (توسيع البحث), model optimization (توسيع البحث)
binary case » binary mask (توسيع البحث), binary image (توسيع البحث), primary case (توسيع البحث)
case design » based design (توسيع البحث), game design (توسيع البحث), core design (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
design optimization » bayesian optimization (توسيع البحث)
guided optimization » based optimization (توسيع البحث), model optimization (توسيع البحث)
binary case » binary mask (توسيع البحث), binary image (توسيع البحث), primary case (توسيع البحث)
case design » based design (توسيع البحث), game design (توسيع البحث), core design (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
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MSE for ILSTM algorithm in binary classification.
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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The Pseudo-Code of the IRBMO Algorithm.
منشور في 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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IRBMO vs. meta-heuristic algorithms boxplot.
منشور في 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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IRBMO vs. feature selection algorithm boxplot.
منشور في 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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IRBMO vs. variant comparison adaptation data.
منشور في 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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Pseudo Code of RBMO.
منشور في 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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12
P-value on CEC-2017(Dim = 30).
منشور في 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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13
Memory storage behavior.
منشور في 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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14
Elite search behavior.
منشور في 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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15
Description of the datasets.
منشور في 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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S and V shaped transfer functions.
منشور في 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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S- and V-Type transfer function diagrams.
منشور في 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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Collaborative hunting behavior.
منشور في 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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Friedman average rank sum test results.
منشور في 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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Summary of LITNET-2020 dataset.
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. …"