Search alternatives:
process optimization » model optimization (Expand Search)
fitness optimization » stress optimization (Expand Search), linear optimization (Expand Search), field optimization (Expand Search)
data process » data processing (Expand Search), damage process (Expand Search), data access (Expand Search)
data fitness » data files (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
process optimization » model optimization (Expand Search)
fitness optimization » stress optimization (Expand Search), linear optimization (Expand Search), field optimization (Expand Search)
data process » data processing (Expand Search), damage process (Expand Search), data access (Expand Search)
data fitness » data files (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
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41
The result of the Wilcoxon test of presented COFFO against compared methods.
Published 2022Subjects: -
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43
Convergence graphs for ten CEC 2019 benchmark functions and direct comparison between COFFO and FFO.
Published 2022Subjects: -
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46
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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47
Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things
Published 2025“…Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …”
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48
Proposed Algorithm.
Published 2025“…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. …”
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49
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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50
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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51
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52
Comparisons between ADAM and NADAM optimizers.
Published 2025“…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. …”
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53
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57
Medium-scale dataset comparative analysis using the number of features selected.
Published 2023Subjects: -
58
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Large-scale dataset comparative analysis using the number of features selected.
Published 2023Subjects: -
60