بدائل البحث:
process optimization » model optimization (توسيع البحث)
design optimization » bayesian optimization (توسيع البحث)
based process » based processes (توسيع البحث), based probes (توسيع البحث), based proteins (توسيع البحث)
linac based » lines based (توسيع البحث)
process optimization » model optimization (توسيع البحث)
design optimization » bayesian optimization (توسيع البحث)
based process » based processes (توسيع البحث), based probes (توسيع البحث), based proteins (توسيع البحث)
linac based » lines based (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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The Pseudo-Code of the IRBMO Algorithm.
منشور في 2025"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"
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IRBMO vs. meta-heuristic algorithms boxplot.
منشور في 2025"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"
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IRBMO vs. feature selection algorithm boxplot.
منشور في 2025"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"
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Algorithm for generating hyperparameter.
منشور في 2024"…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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Results of machine learning algorithm.
منشور في 2024"…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. …"