يعرض 1 - 20 نتائج من 34 نتيجة بحث عن '(( binary arm based optimization algorithm ) OR ( binary e learning optimization algorithm ))', وقت الاستعلام: 0.46s تنقيح النتائج
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    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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    Effects of Class Imbalance and Data Scarcity on the Performance of Binary Classification Machine Learning Models Developed Based on ToxCast/Tox21 Assay Data حسب Changhun Kim (682542)

    منشور في 2022
    "…Therefore, the resampling algorithm employed should vary depending on the data distribution to achieve optimal classification performance. …"
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    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
    "…We fill the gap by developing an iterative matching algorithm for the three-group setting. Our algorithm outperforms the nearest neighbor algorithm and is shown to produce matched samples with total distance no larger than twice the optimal distance. …"
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    A* Path-Finding Algorithm to Determine Cell Connections حسب Max Weng (22327159)

    منشور في 2025
    "…The integration of heuristic optimization and machine learning significantly enhances both speed and precision in astrocyte data analysis. …"
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    Flow diagram of the proposed model. حسب Uğur Ejder (22683228)

    منشور في 2025
    "…<div><p>Machine learning models are increasingly applied to assisted reproductive technologies (ART), yet most studies rely on conventional algorithms with limited optimization. …"
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    Fig 12 - حسب Nisha Yadav (366131)

    منشور في 2024
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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. …"
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    Parameter setting for CBOA and PSO. 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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    NSL-KDD dataset description. 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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    The architecture of LSTM cell. 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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    The architecture of ILSTM. 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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    Parameter setting for LSTM. 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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    LITNET-2020 data splitting approach. 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. …"