Search alternatives:
process optimization » model optimization (Expand Search)
step optimization » after optimization (Expand Search), swarm optimization (Expand Search), based optimization (Expand Search)
data process » data processing (Expand Search), damage process (Expand Search), data access (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data step » data set (Expand Search)
process optimization » model optimization (Expand Search)
step optimization » after optimization (Expand Search), swarm optimization (Expand Search), based optimization (Expand Search)
data process » data processing (Expand Search), damage process (Expand Search), data access (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data step » data set (Expand Search)
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Mean fitness and standard deviation results of compared approaches on CEC2019 benchmark functions.
Published 2022Subjects: -
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The result of the Wilcoxon test of presented COFFO against compared methods.
Published 2022Subjects: -
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Convergence graphs for ten CEC 2019 benchmark functions and direct comparison between COFFO and FFO.
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The Pseudo-Code of the IRBMO Algorithm.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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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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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. …”