Search alternatives:
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
led optimization » lead optimization (Expand Search), yet optimization (Expand Search), based optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
use driven » user driven (Expand Search), us driven (Expand Search), use drives (Expand Search)
based led » based 3d (Expand Search), based log (Expand Search), based l2 (Expand Search)
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
led optimization » lead optimization (Expand Search), yet optimization (Expand Search), based optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
use driven » user driven (Expand Search), us driven (Expand Search), use drives (Expand Search)
based led » based 3d (Expand Search), based log (Expand Search), based l2 (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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2
Proposed Algorithm.
Published 2025“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”
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3
Comparisons between ADAM and NADAM optimizers.
Published 2025“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”
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Flow diagram of the proposed model.
Published 2025“…<div><p>Machine learning models are increasingly applied to assisted reproductive technologies (ART), yet most studies rely on conventional algorithms with limited optimization. This proof-of-concept study investigates whether a hybrid Logistic Regression–Artificial Bee Colony (LR–ABC) framework can enhance predictive performance in in vitro fertilization (IVF) outcomes while producing interpretable, hypothesis-driven associations with nutritional and pharmaceutical supplement use. …”
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An Example of a WPT-MEC Network.
Published 2025“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”
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7
Related Work Summary.
Published 2025“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”
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8
Simulation parameters.
Published 2025“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”
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Training losses for N = 10.
Published 2025“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”
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Normalized computation rate for N = 10.
Published 2025“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”
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11
Summary of Notations Used in this paper.
Published 2025“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”
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Data_Sheet_1_A Data-Driven Framework for Identifying Intensive Care Unit Admissions Colonized With Multidrug-Resistant Organisms.docx
Published 2022“…</p>Materials and Methods<p>Leveraging data from electronic healthcare records and a unique MDRO universal screening program, we developed a data-driven modeling framework to predict MRSA, VRE, and CRE colonization upon intensive care unit (ICU) admission, and identified the associated socio-demographic and clinical factors using logistic regression (LR), random forest (RF), and XGBoost algorithms. …”
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Image 1_A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology.png
Published 2025“…CardioSpectra formulates athlete profiles as multivariate probabilistic entities across latent diagnostic states, using sparsity-aware inference to generate interpretable risk predictions while optimizing a sensitivity-specificity trade-off tailored to clinical priorities. …”
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14
Thesis-RAMIS-Figs_Slides
Published 2024“…In the context of facies recovery using simulations, the task of optimal sampling is formalized and addressed using a maximum information extraction criterion. …”