يعرض 1 - 20 نتائج من 51 نتيجة بحث عن '(( library based case optimization algorithm ) OR ( primary data driven optimization algorithm ))', وقت الاستعلام: 0.59s تنقيح النتائج
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    An optimal solution for the HFS instance. حسب Xiang Tian (4369285)

    منشور في 2025
    "…Next, a CP model (IPMMPO-CP) applicable to multi-scenario HFS problems is proposed. Finally, based on a large number of instances and real cases, IPMMPO-CP is compared with 9 representative algorithms and 2 latest CP models. …"
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    Fine-Tuning a Genetic Algorithm for CAMD: A Screening-Guided Warm Start حسب Yifan Wang (380120)

    منشور في 2025
    "…In response to these challenges, this work presents a method to fine-tune a genetic algorithm for CAMD. The proposed method builds on the COSMO-CAMD framework that utilizes a genetic algorithm for solving optimization-based molecular design problems and COSMO-RS for predicting physical properties of molecules. …"
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    Fine-Tuning a Genetic Algorithm for CAMD: A Screening-Guided Warm Start حسب Yifan Wang (380120)

    منشور في 2025
    "…In response to these challenges, this work presents a method to fine-tune a genetic algorithm for CAMD. The proposed method builds on the COSMO-CAMD framework that utilizes a genetic algorithm for solving optimization-based molecular design problems and COSMO-RS for predicting physical properties of molecules. …"
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    Comparison based on hard instances from [79]. حسب Xiang Tian (4369285)

    منشور في 2025
    "…Next, a CP model (IPMMPO-CP) applicable to multi-scenario HFS problems is proposed. Finally, based on a large number of instances and real cases, IPMMPO-CP is compared with 9 representative algorithms and 2 latest CP models. …"
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    Table_1_Data-based modeling for hypoglycemia prediction: Importance, trends, and implications for clinical practice.docx حسب Liyin Zhang (6371999)

    منشور في 2023
    "…Models utilizing clinical data have identified a variety of risk factors that can lead to hypoglycemic events. Data-driven models based on various techniques such as neural networks, autoregressive, ensemble learning, supervised learning, and mathematical formulas have also revealed suggestive features in cases of hypoglycemia prediction.…"
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