Showing 161 - 180 results of 195 for search '(( binary scale based optimization algorithm ) OR ( binary data modeling optimization algorithm ))', query time: 0.53s Refine Results
  1. 161

    Flowchart scheme of the ML-based model. by Noshaba Qasmi (20405009)

    Published 2024
    “…<b>J)</b> Optimization of hyperparameter tuning. <b>K)</b> Algorithm selection from all models. …”
  2. 162
  3. 163

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

    Published 2024
    “…In addition, the practical benefits for \emph{<i>MPS</i>} in the context of simulating channelized facies models is demonstrated using synthetic data and real geological facies. …”
  4. 164

    Confusion matrix. by Yixian Wen (12201388)

    Published 2025
    “…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
  5. 165

    Parameter settings. by Yixian Wen (12201388)

    Published 2025
    “…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
  6. 166

    Dynamic resource allocation process. by Yixian Wen (12201388)

    Published 2025
    “…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”
  7. 167

    Data_Sheet_1_Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer.pdf by Maliheh Aramon (6557906)

    Published 2019
    “…Our results suggest an improved scaling over the other algorithms for fully connected problems of average difficulty with bimodal disorder. …”
  8. 168

    Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf by Muhammad Awais (263096)

    Published 2024
    “…To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …”
  9. 169

    Models and Dataset by M RN (9866504)

    Published 2025
    “…</p><p dir="ltr"><br></p><p dir="ltr"><b>TJO (Tom and Jerry Optimization):</b><br>TJO is a nature-inspired metaheuristic algorithm that models the predator-prey dynamics of the cartoon characters Tom (predator) and Jerry (prey). …”
  10. 170

    Natural language processing for automated quantification of bone metastases reported in free-text bone scintigraphy reports by Olivier Q. Groot (9370461)

    Published 2020
    “…Pending external validation, the NLP algorithm developed in this study may be implemented as a means to aid researchers in tackling large amounts of data.…”
  11. 171
  12. 172

    Seed mix selection model by Bethanne Bruninga-Socolar (10923639)

    Published 2022
    “…</p> <p>  </p> <p>We applied the seed mix selection model using a binary genetic algorithm to select seed mixes (R package ‘GA’; Scrucca 2013; Scrucca 2017). …”
  13. 173
  14. 174

    Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat. by Enrico Bertozzi (22461709)

    Published 2025
    “…Both the SVM model with a linear kernel and the one with an RBF kernel achieved identical results. Optimization with GridSearchCV corroborated this stagnation, identifying a simple linear model (C=0.05, gamma='scale') as the optimal configuration, indicating that the additional complexity of nonlinear kernels did not confer predictive gains. …”
  15. 175

    DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx by Massaine Bandeira e Sousa (7866242)

    Published 2024
    “…Two NIRs devices, the portable QualitySpec® Trek (QST) and the benchtop NIRFlex N-500 were used to collect spectral data. Classification of genotypes was carried out using the K-nearest neighbor algorithm (KNN) and partial least squares (PLS) models. …”
  16. 176

    Bayesian sequential design for sensitivity experiments with hybrid responses by Yuxia Liu (1779592)

    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. …”
  17. 177

    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. …”
  18. 178

    Steps in the extraction of 14 coordinates from the CT slices for the curved MPR. by Linus Woitke (22783534)

    Published 2025
    “…Protruding paths are then eliminated using graph-based optimization algorithms, as demonstrated in f). …”
  19. 179

    Sample image for illustration. by Indhumathi S. (19173013)

    Published 2024
    “…The results demonstrate that CBFD achieves a average precision of 0.97 for the test image, outperforming Superpoint, Directional Intensified Tertiary Filtering (DITF), Binary Robust Independent Elementary Features (BRIEF), Binary Robust Invariant Scalable Keypoints (BRISK), Speeded Up Robust Features (SURF), and Scale Invariant Feature Transform (SIFT), which achieve scores of 0.95, 0.92, 0.72, 0.66, 0.63 and 0.50 respectively. …”
  20. 180

    Comparison analysis of computation time. by Indhumathi S. (19173013)

    Published 2024
    “…The results demonstrate that CBFD achieves a average precision of 0.97 for the test image, outperforming Superpoint, Directional Intensified Tertiary Filtering (DITF), Binary Robust Independent Elementary Features (BRIEF), Binary Robust Invariant Scalable Keypoints (BRISK), Speeded Up Robust Features (SURF), and Scale Invariant Feature Transform (SIFT), which achieve scores of 0.95, 0.92, 0.72, 0.66, 0.63 and 0.50 respectively. …”