بدائل البحث:
learning optimization » learning motivation (توسيع البحث), lead optimization (توسيع البحث)
code optimization » codon optimization (توسيع البحث), model optimization (توسيع البحث), dose optimization (توسيع البحث)
also learning » a learning (توسيع البحث), l2 learning (توسيع البحث), shallow learning (توسيع البحث)
primary data » primary care (توسيع البحث)
data code » data model (توسيع البحث), data came (توسيع البحث)
learning optimization » learning motivation (توسيع البحث), lead optimization (توسيع البحث)
code optimization » codon optimization (توسيع البحث), model optimization (توسيع البحث), dose optimization (توسيع البحث)
also learning » a learning (توسيع البحث), l2 learning (توسيع البحث), shallow learning (توسيع البحث)
primary data » primary care (توسيع البحث)
data code » data model (توسيع البحث), data came (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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Results of machine learning algorithm.
منشور في 2024"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
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ROC comparison of machine learning algorithm.
منشور في 2024"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
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Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm
منشور في 2025"…Our results show that deep learning and optimization </p><p dir="ltr">methods, such as the binary GWO algorithm, can be successfully applied to melanoma diagnosis. …"
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Algorithm for generating hyperparameter.
منشور في 2024"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
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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. …"