يعرض 21 - 34 نتائج من 34 نتيجة بحث عن '(( algorithm co function ) OR ( algorithm transfer function ))*', وقت الاستعلام: 0.08s تنقيح النتائج
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    A Quasi-Oppositional Method for Output Tracking Control by Swarm-Based MPID Controller on AC/HVDC Interconnected Systems With Virtual Inertia Emulation حسب Iman M. Hosseini Naveh (16891482)

    منشور في 2021
    "…Also the proposed fitness function, as deviation characteristics of the step response in MIMO transfer function in virtual inertia emulation based HVDC model, is compared with integral time absolute error (ITAE), as the standard performance index in the optimization process. …"
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    Don't understand a measure? Learn it: Structured Prediction for Coreference Resolution optimizing its measures حسب Iryna Haponchyk (19691701)

    منشور في 2017
    "…The accurate model comparison on the standard CoNLL-2012 setting shows the benefit of more expressive loss functions.…"
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    Reinforcement Learning-Based School Energy Management System حسب Yassine Chemingui (18891757)

    منشور في 2020
    "…In recent years, the Deep Reinforcement Learning algorithm, applying neural networks for function approximation, shows promising results in handling such complex problems. …"
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    Gas pipeline modelling and control حسب Whalley, R

    منشور في 2015
    "…The pipeline input–output, transfer function, pressure and volume flow representations are formulated. …"
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    A lightweight adaptive compression scheme for energy-efficient mobile-to-mobile file sharing applications حسب Sharafeddine, Sanaa

    منشور في 2011
    "…The proposed scheme monitors the signal strength level during the file transfer process and compresses data blocks on-the-fly only whenever energy reduction gain is expected. …"
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    Automatic image quality evaluation in digital radiography using a modified version of the IAEA radiography phantom allowing multiple detection tasks حسب Ioannis A. Tsalafoutas (14776939)

    منشور في 2025
    "…</p><h3>Results</h3><p dir="ltr">The IQ‐metric values calculated using the modified IAEA phantom images can be radically different between raw and clinical images, and between different manufacturers, irrespectively whether only the standard or all the different Al‐target thicknesses are considered. The modulation transfer function (MTF) and the signal‐to‐noise‐ratio (SNR) dependence on exposure conditions and post‐processing algorithms do not always follow the same trends for raw and clinical images and/or different manufacturers, while the signal‐difference‐to‐noise‐ratio (SDNR) and the detectability index (d′), despite their differences, seem more appropriate to characterize IQ. …"
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