The result of the best fitness value, mean fitness value, standard deviation of fitness value and feature selection ratio of algorithms on the COVID-19 dataset. حسب Nebojsa Bacanin (13932723)

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Random forest model performs better than support vector machine algorithms and when it primarily uses spontaneous photopic ERG of 60-s duration in humans. حسب Ramsés Noguez Imm (6658637)

UK Biobank data wrangling statistics and results. حسب Simeone Marino (81051)

CEC 2019 benchmark characteristics. حسب Nebojsa Bacanin (13932723)

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Results of Holm’s step-down procedure. حسب Nebojsa Bacanin (13932723)

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Friedman ranks of tested methods on CEC2019 benchmark functions. حسب Nebojsa Bacanin (13932723)

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V-shaped transfer functions. حسب Nebojsa Bacanin (13932723)

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Resilts of Friedman and Iman-Davenport tests (<i>α</i> = 0.05). حسب Nebojsa Bacanin (13932723)

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Mean fitness and standard deviation results of compared approaches on CEC2019 benchmark functions. حسب Nebojsa Bacanin (13932723)

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Error rate convergence graphs. حسب Nebojsa Bacanin (13932723)

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COVID-19 dataset description. حسب Nebojsa Bacanin (13932723)

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Control parameter settings for comparative feature selection methods. حسب Nebojsa Bacanin (13932723)

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The result of the Wilcoxon test of presented COFFO against compared methods. حسب Nebojsa Bacanin (13932723)

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COFFO control parameters. حسب Nebojsa Bacanin (13932723)

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Convergence graphs for ten CEC 2019 benchmark functions and direct comparison between COFFO and FFO. حسب Nebojsa Bacanin (13932723)

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Proposed Algorithm. حسب Hend Bayoumi (22693738)

"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …"

Reproducing kernel-based semiparametric functional smoothed score estimation with binary responses حسب Meichen Liu (8168148)

Fig 2 - حسب Olaide N. Oyelade (14047002)

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LITNET-2020 data splitting approach. حسب Asmaa Ahmed Awad (16726315)

"…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. …"

Comparisons between ADAM and NADAM optimizers. حسب Hend Bayoumi (22693738)

"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …"