Showing 1 - 6 results of 6 for search '(( binary use driven optimization algorithm ) OR ( library based aor optimization algorithm ))', query time: 0.38s Refine Results
  1. 1

    Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things by Ashok Kumar K (21441108)

    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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    Flow diagram of the proposed model. by Uğur Ejder (22683228)

    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. …”
  4. 4

    Data_Sheet_1_A Data-Driven Framework for Identifying Intensive Care Unit Admissions Colonized With Multidrug-Resistant Organisms.docx by Çaǧlar Çaǧlayan (12253934)

    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. …”
  5. 5

    Image 1_A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology.png by Minjin Guo (22751300)

    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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    Thesis-RAMIS-Figs_Slides by Felipe Santibañez-Leal (10967991)

    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. …”