Search alternatives:
bayesian optimization » based optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
data bayesian » a bayesian (Expand Search), art bayesian (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data model » data models (Expand Search)
bayesian optimization » based optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
data bayesian » a bayesian (Expand Search), art bayesian (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data model » data models (Expand Search)
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Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things
Published 2025“…This research presents Data-Driven Intrusion Detection System in Internet of Things utilizing Optimized Bayesian Regularization-Back Propagation Neural Network (DIDS-BRBPNN-BBWOA-IoT) to overcome these issues. …”
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Bayesian sequential design for sensitivity experiments with hybrid responses
Published 2023“…To deal with the problem of complex computation involved in searching for optimal designs, fast algorithms are presented using two strategies to approximate the optimal criterion, denoted as SI-optimal design and Bayesian D-optimal design, respectively. …”
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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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IRBMO vs. meta-heuristic algorithms boxplot.
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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IRBMO vs. feature selection algorithm boxplot.
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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Effects of Class Imbalance and Data Scarcity on the Performance of Binary Classification Machine Learning Models Developed Based on ToxCast/Tox21 Assay Data
Published 2022“…In this study, the effects of CI and data scarcity (DS) on the performance of binary classification models were investigated using ToxCast bioassay data. …”