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resource optimization » resource utilization (Expand Search), resource utilisation (Expand Search), resource limitations (Expand Search)
whale optimization » swarm optimization (Expand Search)
each resource » health resource (Expand Search), space resource (Expand Search), a resource (Expand Search)
binary each » binary health (Expand Search)
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Showing 1 - 4 results of 4 for search '(( binary each resource optimization algorithm ) OR ( binary task whale optimization algorithm ))', query time: 0.93s Refine Results
  1. 1
    Secure MANET routing with blockchain-enhanced latent encoder coupled GANs and BEPO optimization

    Secure MANET routing with blockchain-enhanced latent encoder coupled GANs and BEPO optimization by Sandeep Jagonda Patil (22048337)

    Published 2025
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  2. 2
    Natural language processing for automated quantification of bone metastases reported in free-text bone scintigraphy reports

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

    Published 2020
    “…The aim of this study was to develop a natural language processing (NLP) algorithm for binary classification (single metastasis versus two or more metastases) in bone scintigraphy reports of patients undergoing surgery for bone metastases.…”
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  3. 3
    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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  4. 4
    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
    “…</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.…”
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