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processing evolution » processing explanation (Expand Search)
evolution algorithms » evolutionary algorithms (Expand Search), evolutionary algorithm (Expand Search), recognition algorithms (Expand Search)
work optimization » wolf optimization (Expand Search), swarm optimization (Expand Search), dose optimization (Expand Search)
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binary health » primary health (Expand Search)
health work » health worker (Expand Search), health workers (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
Showing 1 - 7 results of 7 for search '(( binary health work optimization algorithm ) OR ( binary data processing evolution algorithms ))', query time: 0.41s Refine Results
  1. 1
    Dataset 2: Zip file containing the Tables of the presented method and results

    Dataset 2: Zip file containing the Tables of the presented method and results by Suchismita Behera (22027316)

    Published 2025
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  2. 2
    Optimal Timings Codebook.xlsx

    Optimal Timings Codebook.xlsx by Emma Spillane (11249121)

    Published 2021
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  3. 3
    Optimal Time Intervals of Breech Births Dataset

    Optimal Time Intervals of Breech Births Dataset by Emma Spillane (11249121)

    Published 2021
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  4. 4
    Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP

    Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP by Xiaoyuan Wang (492534)

    Published 2022
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  5. 5
    Data_Sheet_1_Prediction of Mental Health in Medical Workers During COVID-19 Based on Machine Learning.ZIP

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

    Published 2021
    “…Besides, we use stepwise logistic regression, binary bat algorithm, hybrid improved dragonfly algorithm and the proposed prediction model to predict mental health of medical workers. …”
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  6. 6
    Table 1_Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis.docx

    Table 1_Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis.docx by Ali Nabavi (21097424)

    Published 2025
    “…Demographic, clinical, and heavy metal biomarker data (e.g., blood lead and cadmium levels) were analyzed as features, with hearing loss status—defined as a pure-tone average threshold exceeding 25 dB HL across 500, 1,000, 2000, and 4,000 Hz in the better ear—serving as the binary outcome. Multiple machine learning algorithms, including Random Forest, XGBoost, Gradient Boosting, Logistic Regression, CatBoost, and MLP, were optimized and evaluated. …”
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  7. 7
    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. …”
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