Showing 181 - 200 results of 206 for search '(( dietary data processing optimization algorithm ) OR ( binary a based optimization algorithm ))', query time: 0.34s Refine Results
  1. 181

    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. 182
  3. 183

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

    Published 2023
    “…<p>In experimental design, a common problem seen in practice is when the result includes one binary response and multiple continuous responses. …”
  4. 184

    Psoas muscle CT radiomics-based machine learning models to predict response to infliximab in patients with Crohn’s disease by Zhuoyan Chen (12193358)

    Published 2025
    “…<i>Z</i> score standardization and independent sample <i>t</i> test were applied to identify optimal predictive features, which were then utilized in seven ML algorithms for training and validation. …”
  5. 185

    Data_Sheet_1_Prediction of Mental Health in Medical Workers During COVID-19 Based on Machine Learning.ZIP by Xiaofeng Wang (119575)

    Published 2021
    “…In this study, we propose a novel prediction model based on optimization algorithm and neural network, which can select and rank the most important factors that affect mental health of medical workers. …”
  6. 186

    DataSheet_1_Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.docx by Yuhong Huang (115702)

    Published 2021
    “…</p>Conclusions<p>Multi-parametric MRI-based radiomics combining with machine learning approaches provide a promising method to predict the molecular subtype and AR expression of breast cancer non-invasively.…”
  7. 187

    Data Sheet 1_Detection of litchi fruit maturity states based on unmanned aerial vehicle remote sensing and improved YOLOv8 model.docx by Changjiang Liang (21099887)

    Published 2025
    “…To address these limitations, this study proposed a method for detecting litchi maturity states based on UAV remote sensing and YOLOv8-FPDW. …”
  8. 188

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

    Published 2025
    “…In e), the image is skeletonized by creating a line along the center of the lower jaw. Protruding paths are then eliminated using graph-based optimization algorithms, as demonstrated in f). …”
  9. 189

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

    Published 2024
    “…This article introduces a Convex Based Feature Descriptor (CBFD) system designed to withstand rotation, lighting, and blur variations while remaining computationally efficient. …”
  10. 190

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

    Published 2024
    “…This article introduces a Convex Based Feature Descriptor (CBFD) system designed to withstand rotation, lighting, and blur variations while remaining computationally efficient. …”
  11. 191

    Process flow diagram of CBFD. by Indhumathi S. (19173013)

    Published 2024
    “…This article introduces a Convex Based Feature Descriptor (CBFD) system designed to withstand rotation, lighting, and blur variations while remaining computationally efficient. …”
  12. 192

    Precision recall curve. by Indhumathi S. (19173013)

    Published 2024
    “…This article introduces a Convex Based Feature Descriptor (CBFD) system designed to withstand rotation, lighting, and blur variations while remaining computationally efficient. …”
  13. 193

    Quadratic polynomial in 2D image plane. by Indhumathi S. (19173013)

    Published 2024
    “…This article introduces a Convex Based Feature Descriptor (CBFD) system designed to withstand rotation, lighting, and blur variations while remaining computationally efficient. …”
  14. 194

    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.…”
  15. 195

    Models and Dataset by M RN (9866504)

    Published 2025
    “…</p><p dir="ltr"><br></p><p dir="ltr"><b>RAO (Rao Optimization Algorithm):</b><br>RAO is a parameter-less optimization algorithm that updates solutions based on simple arithmetic operations involving the best and worst individuals in the population. …”
  16. 196

    Processed dataset to train and test the WGAN-GP_IMOA_DA_Ensemble model by Ramya Chinnasamy (21633527)

    Published 2025
    “…This framework integrates a novel biologically inspired optimization algorithm, the Indian Millipede Optimization Algorithm (IMOA), for effective feature selection. …”
  17. 197

    30-Meter Resolution Dataset of Abandoned and Reclaimed Croplands in Inner Mongolia, China (2000-2022) by Deji Wuyun (18440981)

    Published 2024
    “…This method enables precise classification of cultivation status and adopts a binary classification strategy with adaptive optimization, improving the efficiency of sample generation for the Random Forest algorithm. …”
  18. 198

    Table_1_iRNA5hmC: The First Predictor to Identify RNA 5-Hydroxymethylcytosine Modifications Using Machine Learning.docx by Yuan Liu (88411)

    Published 2020
    “…In this predictor, we introduced a sequence-based feature algorithm consisting of two feature representations, (1) k-mer spectrum and (2) positional nucleotide binary vector, to capture the sequential characteristics of 5hmC sites. …”
  19. 199

    Supplementary Material 8 by Nishitha R Kumar (19750617)

    Published 2025
    “…</li><li><b>Naïve bayes (NB): </b> A probabilistic classifier based on Bayes' theorem, suitable for predicting resistance phenotypes based on genomic features.…”
  20. 200

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

    Published 2024
    “…The accuracy of the optimal scenario for classifying samples with a cooking time of 30 minutes reached RCal2  = 0.86 and RVal2 = 0.84, with a Kappa value of 0.53. …”