Search alternatives:
processing optimization » process optimization (Expand Search), process optimisation (Expand Search), routing optimization (Expand Search)
data processing » image processing (Expand Search)
a optimization » ai optimization (Expand Search), _ optimization (Expand Search), b optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data a » data _ (Expand Search), data 1 (Expand Search), data b (Expand Search)
processing optimization » process optimization (Expand Search), process optimisation (Expand Search), routing optimization (Expand Search)
data processing » image processing (Expand Search)
a optimization » ai optimization (Expand Search), _ optimization (Expand Search), b optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data a » data _ (Expand Search), data 1 (Expand Search), data b (Expand Search)
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a) Accuracy and b) selected feature size of algorithms on the COVID-19 dataset.
Published 2022Subjects: -
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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. …”
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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. 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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<i>hi</i>PRS algorithm process flow.
Published 2023“…<b>(C)</b> The whole training data is then scanned, searching for these sequences and deriving a re-encoded dataset where interaction terms are binary features (i.e., 1 if sequence <i>i</i> is observed in <i>j</i>-th patient genotype, 0 otherwise). …”
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A* Path-Finding Algorithm to Determine Cell Connections
Published 2025“…To address this, the research integrates a modified A* pathfinding algorithm with a U-Net convolutional neural network, a custom statistical binary classification method, and a personalized Min-Max connectivity threshold to automate the detection of astrocyte connectivity.…”
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The flowchart of the proposed algorithm.
Published 2024“…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
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