Search alternatives:
group classification » risk classification (Expand Search), improve classification (Expand Search), perform classification (Expand Search)
based optimization » whale optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
binary task » binary mask (Expand Search)
data group » ta group (Expand Search)
task based » risk based (Expand Search)
group classification » risk classification (Expand Search), improve classification (Expand Search), perform classification (Expand Search)
based optimization » whale optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
binary task » binary mask (Expand Search)
data group » ta group (Expand Search)
task based » risk based (Expand Search)
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Proposed Algorithm.
Published 2025“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”
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Comparisons between ADAM and NADAM optimizers.
Published 2025“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”
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The Pseudo-Code of the IRBMO Algorithm.
Published 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. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”
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IRBMO vs. meta-heuristic algorithms boxplot.
Published 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. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”
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IRBMO vs. feature selection algorithm boxplot.
Published 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. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”
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Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf
Published 2020“…In this way, for each binary problem, the CSP algorithm produces features to determine if the specific body part is engaged in the task or not. …”
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Data Sheet 1_Bundled assessment to replace on-road test on driving function in stroke patients: a binary classification model via random forest.docx
Published 2025“…A random forest algorithm was then applied to construct a binary classification model based on the data obtained from the two groups.…”
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An Example of a WPT-MEC Network.
Published 2025“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”
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Related Work Summary.
Published 2025“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”
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Simulation parameters.
Published 2025“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”