يعرض 1 - 20 نتائج من 22 نتيجة بحث عن '(( binary part model optimization algorithm ) OR ( primary data driven optimization algorithm ))*', وقت الاستعلام: 0.54s تنقيح النتائج
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    Data used to drive the Double Layer Carbon Model in the Qinling Mountains. حسب Huiwen Li (17705280)

    منشور في 2024
    "…The model divides the soil profile into topsoil (0-20 cm) and subsoil (20–100 cm) layers to match the SOC maps of the corresponding two layers generated by data-driven models. Each of these layers contains a young carbon pool (CY) with a higher decomposition rate and an old carbon pool (CO) with a lower decomposition rate. …"
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    Label-Free Assessment of the Drug Resistance of Epithelial Ovarian Cancer Cells in a Microfluidic Holographic Flow Cytometer Boosted through Machine Learning حسب Lu Xin (728966)

    منشور في 2021
    "…Furthermore, it reflects strong potentialities to develop data-driven individualized chemotherapy treatments in the future.…"
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    Label-Free Assessment of the Drug Resistance of Epithelial Ovarian Cancer Cells in a Microfluidic Holographic Flow Cytometer Boosted through Machine Learning حسب Lu Xin (728966)

    منشور في 2021
    "…Furthermore, it reflects strong potentialities to develop data-driven individualized chemotherapy treatments in the future.…"
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    Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf حسب Muhammad Awais (263096)

    منشور في 2024
    "…To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …"
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    Thesis-RAMIS-Figs_Slides حسب Felipe Santibañez-Leal (10967991)

    منشور في 2024
    "…Importantly, this strategy locates samples adaptively on the transition between facies which improves the performance of conventional \emph{<i>MPS</i>} algorithms. In conclusion, this work shows that preferential sampling can contribute in \emph{<i>MPS</i>} even at very small sampling regimes and, as a corollary, demonstrates that prior models (obtained form a training image) can be used effectively not only to simulate non-sensed variables of the field, but to decide where to measure next.…"
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