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function optimization » reaction optimization (Expand Search), formulation optimization (Expand Search), generation optimization (Expand Search)
evolution algorithms » evolutionary algorithms (Expand Search), evolutionary algorithm (Expand Search), recognition algorithms (Expand Search)
process evolution » process evaluation (Expand Search), process regulation (Expand Search), stress evolution (Expand Search)
heart function » graft function (Expand Search)
binary heart » binary health (Expand Search), binary depot (Expand Search)
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Showing 1 - 4 results of 4 for search '(( binary heart function optimization algorithm ) OR ( binary data process evolution algorithms ))', query time: 0.46s 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
    Multicategory Angle-Based Learning for Estimating Optimal Dynamic Treatment Regimes With Censored Data

    Multicategory Angle-Based Learning for Estimating Optimal Dynamic Treatment Regimes With Censored Data by Fei Xue (24567)

    Published 2021
    “…Specifically, the proposed method obtains the optimal DTR via integrating estimations of decision rules at multiple stages into a single multicategory classification algorithm without imposing additional constraints, which is also more computationally efficient and robust. …”
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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
    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
    “…Decision trees were constructed by a hierarchical binary recursive partitioning algorithm to predict the BP-lowering of 10–30% off the maximal value when antihypertensive treatment was given in patients with an extremely high BP (above 220/110 or 180/105 mmHg for patients receiving thrombolysis), according to the American Heart Association/American Stroke Association (AHA/ASA), the European Society of Cardiology, and the European Society of Hypertension (ESC/ESH) guidelines. …”
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