Search alternatives:
features optimization » feature optimization (Expand Search), mixture optimization (Expand Search), resource optimization (Expand Search)
based optimization » whale optimization (Expand Search)
tasks based » task based (Expand Search), cases based (Expand Search)
b features » _ features (Expand Search), 5 features (Expand Search), b feature (Expand Search)
binary b » binary _ (Expand Search)
features optimization » feature optimization (Expand Search), mixture optimization (Expand Search), resource optimization (Expand Search)
based optimization » whale optimization (Expand Search)
tasks based » task based (Expand Search), cases based (Expand Search)
b features » _ features (Expand Search), 5 features (Expand Search), b feature (Expand Search)
binary b » binary _ (Expand Search)
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Feature selection results.
Published 2025“…Further integrate the binary variant of OcOA (bOcOA) for effective feature selection, which reduces the average classification error to 0.4237 and increases CNN accuracy to 93.48%. …”
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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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Flowchart scheme of the ML-based model.
Published 2024“…<b>Fii)</b> Texture information using local binary patterns. …”
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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. …”