Search alternatives:
dose optimization » based optimization (Expand Search), model optimization (Expand Search), wolf optimization (Expand Search)
binary role » binary people (Expand Search), binary relief (Expand Search), primary role (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data dose » data due (Expand Search), data de (Expand Search)
dose optimization » based optimization (Expand Search), model optimization (Expand Search), wolf optimization (Expand Search)
binary role » binary people (Expand Search), binary relief (Expand Search), primary role (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data dose » data due (Expand Search), data de (Expand Search)
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MSE for ILSTM algorithm in binary classification.
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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DataSheet1_Quantum-inspired optimization for wavelength assignment.PDF
Published 2023“…We propose an advanced embedding procedure to transform this problem into the quadratic unconstrained binary optimization (QUBO) form, having a improvement in the number of iterations with price-to-pay being a slight increase in the number of variables (“spins”). …”
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Summary of LITNET-2020 dataset.
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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SHAP analysis for LITNET-2020 dataset.
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. …”