Search alternatives:
access optimization » process optimization (Expand Search), stress optimization (Expand Search), process optimisation (Expand Search)
based optimization » whale optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data access » data across (Expand Search), water access (Expand Search)
data based » data used (Expand Search)
Showing 101 - 108 results of 108 for search '(( binary data based optimization algorithm ) OR ( binary data access optimization algorithm ))', query time: 0.37s Refine Results
  1. 101
    DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx

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

    Published 2024
    “…Cooking data were classified into binary and multiclass variables (CT4C and CT6C). …”
    Save to List
    Saved in:
  2. 102
    DataSheet_1_Exploring deep learning radiomics for classifying osteoporotic vertebral fractures in X-ray images.docx

    DataSheet_1_Exploring deep learning radiomics for classifying osteoporotic vertebral fractures in X-ray images.docx by Jun Zhang (48506)

    Published 2024
    Save to List
    Saved in:
  3. 103
    Models and Dataset

    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. …”
    Save to List
    Saved in:
  4. 104
    Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx

    Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx by Massaine Bandeira e Sousa (7866242)

    Published 2024
    “…Cooking data were classified into binary and multiclass variables (CT4C and CT6C). …”
    Save to List
    Saved in:
  5. 105
    Supplementary Material 8

    Supplementary Material 8 by Nishitha R Kumar (19750617)

    Published 2025
    “…</li><li><b>XGboost: </b>An optimized gradient boosting algorithm that efficiently handles large genomic datasets, commonly used for high-accuracy predictions in <i>E. coli</i> classification.…”
    Save to List
    Saved in:
  6. 106
    Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles

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

    Published 2025
    “…Data sources included peer-reviewed publications and reputable open-access repositories such as the NanoPharos database. …”
    Save to List
    Saved in:
  7. 107
    Seed mix selection model

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

    Published 2022
    “…The genetic algorithm then operated over 1000 iterations, applying crossover and mutation processes to optimize bee richness. …”
    Save to List
    Saved in:
  8. 108
    Flow diagram of the automatic animal detection and background reconstruction.

    Flow diagram of the automatic animal detection and background reconstruction. by David Tadres (9120564)

    Published 2020
    “…(E) The threshold value is calculated based on the histogram: it is the mean of the image subtracted by 4 (optimal value defined by trial and error). …”
    Save to List
    Saved in:

Search Tools: