Showing 41 - 46 results of 46 for search '(( binary phase process optimization algorithm ) OR ( primary data dose optimization algorithm ))', query time: 0.33s Refine Results
  1. 41

    The performance of classifiers. by Sepideh Zununi Vahed (9861298)

    Published 2024
    “…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …”
  2. 42
  3. 43

    Fortran & C++: design fractal-type optical diffractive element by I-Lin Ho (13768960)

    Published 2022
    “…</p> <p>(2) calculate diffraction fields for fractal and/or grid-matrix (binary) phase-holograms.</p> <p>(3) optimize the fractal and/or grid-matrix holograms for given target diffraction images, using annealing algorithms. …”
  4. 44

    Active Learning Accelerated Discovery of Stable Iridium Oxide Polymorphs for the Oxygen Evolution Reaction by Raul A. Flores (2910539)

    Published 2020
    “…We emphasize that the proposed AL algorithm can be easily generalized to search for any binary metal oxide structure with a defined stoichiometry.…”
  5. 45

    Supplementary Material for: The Therapeutic Evaluation of Steroids in IgA Nephropathy Global (TESTING) Study: Trial Design and Baseline Characteristics by Wong M.G. (11640685)

    Published 2021
    “…By the time the excess of serious infections was observed, 262 participants had been randomized to the original full-dose treatment algorithm, and an interim analysis was reported in 2016. …”
  6. 46

    Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles by Soham Savarkar (21811825)

    Published 2025
    “…</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…”