Search alternatives:
initialization algorithm » optimization algorithms (Expand Search), maximization algorithm (Expand Search), identification algorithm (Expand Search)
weight initialization » weight optimization (Expand Search)
based optimization » whale optimization (Expand Search)
binary last » binary mask (Expand Search), binary plddt (Expand Search)
last based » least biased (Expand Search), plant based (Expand Search), laser based (Expand Search)
initialization algorithm » optimization algorithms (Expand Search), maximization algorithm (Expand Search), identification algorithm (Expand Search)
weight initialization » weight optimization (Expand Search)
based optimization » whale optimization (Expand Search)
binary last » binary mask (Expand Search), binary plddt (Expand Search)
last based » least biased (Expand Search), plant based (Expand Search), laser based (Expand Search)
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The architecture of ILSTM.
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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Parameter setting for LSTM.
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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LITNET-2020 data splitting approach.
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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Transformation of symbolic features in NSL-KDD.
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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30-Meter Resolution Dataset of Abandoned and Reclaimed Croplands in Inner Mongolia, China (2000-2022)
Published 2024“…This method enables precise classification of cultivation status and adopts a binary classification strategy with adaptive optimization, improving the efficiency of sample generation for the Random Forest algorithm. …”