Search alternatives:
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
yet optimization » art optimization (Expand Search), lead optimization (Expand Search), path optimization (Expand Search)
primary data » primary care (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based driven » based diet (Expand Search), wave driven (Expand Search), user driven (Expand Search)
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
yet optimization » art optimization (Expand Search), lead optimization (Expand Search), path optimization (Expand Search)
primary data » primary care (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based driven » based diet (Expand Search), wave driven (Expand Search), user driven (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“…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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the functioning of BRPSO.
Published 2025“…A sensitivity analysis of key RFD parameters, including frictional moment and rigid beam length, highlights their influence on seismic performance. The optimization problem is formulated based on the seismic energy dissipation concept, employing a modified binary and real-coded particle swarm optimization (BRPSO) algorithm. …”
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Characteristic of 6- and 10-story SMRF [99,98].
Published 2025“…A sensitivity analysis of key RFD parameters, including frictional moment and rigid beam length, highlights their influence on seismic performance. The optimization problem is formulated based on the seismic energy dissipation concept, employing a modified binary and real-coded particle swarm optimization (BRPSO) algorithm. …”
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The RFD’s behavior mechanism (2002).
Published 2025“…A sensitivity analysis of key RFD parameters, including frictional moment and rigid beam length, highlights their influence on seismic performance. The optimization problem is formulated based on the seismic energy dissipation concept, employing a modified binary and real-coded particle swarm optimization (BRPSO) algorithm. …”
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The relationship between the prevalence of PE and failure rate of each diagnostic strategy.
Published 2022Subjects: -
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Forest plot of failure rate and efficiency of the diagnostic strategies across healthcare settings.
Published 2022Subjects: -
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The relationship between the prevalence of PE and efficiency of each diagnostic strategy.
Published 2022Subjects: -
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Sensitivity and specificity of diagnostic strategies across healthcare settings.
Published 2022Subjects: -
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Machine Learning-Driven Kinetic Elucidation for Sustainable Solvent-Free Continuous ε‑Caprolactone Production via Propionaldehyde-Mediated Nanocarbon Catalysis
Published 2025“…A kinetic model was established by focusing on two primary reactions: Cy = O oxidation (Reaction I) and PRA auto-oxidation (Reaction II), from which the reliable kinetic parameters were obtained via genetic algorithm-based optimization. …”
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Machine Learning-Driven Kinetic Elucidation for Sustainable Solvent-Free Continuous ε‑Caprolactone Production via Propionaldehyde-Mediated Nanocarbon Catalysis
Published 2025“…A kinetic model was established by focusing on two primary reactions: Cy = O oxidation (Reaction I) and PRA auto-oxidation (Reaction II), from which the reliable kinetic parameters were obtained via genetic algorithm-based optimization. …”
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Table_1_Screening of Long Non-coding RNAs Biomarkers for the Diagnosis of Tuberculosis and Preliminary Construction of a Clinical Diagnosis Model.docx
Published 2022“…Background<p>Pathogenic testing for tuberculosis (TB) is not yet sufficient for early and differential clinical diagnosis; thus, we investigated the potential of screening long non-coding RNAs (lncRNAs) from human hosts and using machine learning (ML) algorithms combined with electronic health record (EHR) metrics to construct a diagnostic model.…”