بدائل البحث:
based optimization » whale optimization (توسيع البحث)
ii optimization » ai optimization (توسيع البحث), ivy optimization (توسيع البحث), _ optimization (توسيع البحث)
binary case » binary mask (توسيع البحث), binary image (توسيع البحث), primary case (توسيع البحث)
case based » made based (توسيع البحث), game based (توسيع البحث), rate based (توسيع البحث)
class ii » class c (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
ii optimization » ai optimization (توسيع البحث), ivy optimization (توسيع البحث), _ optimization (توسيع البحث)
binary case » binary mask (توسيع البحث), binary image (توسيع البحث), primary case (توسيع البحث)
case based » made based (توسيع البحث), game based (توسيع البحث), rate based (توسيع البحث)
class ii » class c (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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Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things
منشور في 2025"…Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …"
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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. …"
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SHAP analysis for 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. …"