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process optimization » model optimization (Expand Search)
robust optimization » robust estimation (Expand Search), joint optimization (Expand Search)
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Showing 81 - 92 results of 92 for search '(( binary based process optimization algorithm ) OR ( binary data robust optimization algorithm ))*', query time: 0.52s Refine Results
  1. 81
    Flowchart of software workflow.

    Flowchart of software workflow. by Gavrielle R. Untracht (11820311)

    Published 2021
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  2. 82
    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). …”
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  3. 83
    Data_Sheet_1_The impact of family urban integration on migrant worker mental health in China.docx

    Data_Sheet_1_The impact of family urban integration on migrant worker mental health in China.docx by Xiaotong Sun (6535064)

    Published 2024
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  4. 84
    Data Sheet 1_Detection of litchi fruit maturity states based on unmanned aerial vehicle remote sensing and improved YOLOv8 model.docx

    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
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  5. 85
    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). …”
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  6. 86
    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. …”
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  7. 87
    Table_1_iRNA5hmC: The First Predictor to Identify RNA 5-Hydroxymethylcytosine Modifications Using Machine Learning.docx

    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. …”
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  8. 88
    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.…”
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  9. 89
    Active Learning Accelerated Discovery of Stable Iridium Oxide Polymorphs for the Oxygen Evolution Reaction

    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.…”
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  10. 90
    Seed mix selection model

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

    Published 2022
    “…Classic genetic algorithms consider a population of chromosomes and apply principles of natural selection (selection, mutation, and crossover processes) to generate optimal solutions. …”
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  11. 91
    Image 1_A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology.png

    Image 1_A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology.png by Minjin Guo (22751300)

    Published 2025
    “…Introduction<p>The increasing complexity of athlete cardiovascular risk profiles, coupled with evolving demands in pre-participation screening, necessitates robust, interpretable, and physiologically grounded assessment tools. …”
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  12. 92
    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
    “…Details on the data sourcing process, prompt engineering strategies for large language model (LLM)-based extraction, and validation protocols are provided in the Supplementary Information section.…”
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