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Showing 1 - 7 results of 7 for search '(( binary last based optimization algorithm ) OR ( binary values table optimization algorithm ))*', query time: 0.57s Refine Results
  1. 1
    Binary contingency table.

    Binary contingency table. by Lu Xiao (314030)

    Published 2024
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  2. 2
    Comparison table of the proposed model.

    Comparison table of the proposed model. by Balraj Preet Kaur (20370832)

    Published 2024
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  3. 3
    An intelligent decision-making system for embryo transfer in reproductive technology: a machine learning-based approach

    An intelligent decision-making system for embryo transfer in reproductive technology: a machine learning-based approach by Sanaa Badr (20628838)

    Published 2025
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  4. 4
    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
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  5. 5
    Table_1_Machine Learning Techniques in Blood Pressure Management During the Acute Phase of Ischemic Stroke.DOCX

    Table_1_Machine Learning Techniques in Blood Pressure Management During the Acute Phase of Ischemic Stroke.DOCX by Orit Mazza (12081914)

    Published 2022
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  6. 6
    Table 1_Creating an interactive database for nasopharyngeal carcinoma management: applying machine learning to evaluate metastasis and survival.docx

    Table 1_Creating an interactive database for nasopharyngeal carcinoma management: applying machine learning to evaluate metastasis and survival.docx by Yanbo Sun (2202439)

    Published 2024
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  7. 7
    30-Meter Resolution Dataset of Abandoned and Reclaimed Croplands in Inner Mongolia, China (2000-2022)

    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. …”
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