يعرض 1 - 20 نتائج من 6,956 نتيجة بحث عن '(((( learning strategy decrease ) OR ( a larger decrease ))) OR ( _ values decrease ))', وقت الاستعلام: 0.52s تنقيح النتائج
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    The introduction of mutualisms into assembled communities increases their connectance and complexity while decreasing their richness. حسب Gui Araujo (22170819)

    منشور في 2025
    "…Parameter values: interaction strengths were drawn from a half-normal distribution of zero mean and a standard deviation of 0.2, and strength for consumers was made no larger than the strength for resources. …"
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    A Locally Linear Dynamic Strategy for Manifold Learning. حسب Weifan Wang (4669081)

    منشور في 2025
    "…For 10-30% noise, where the Hebbian network employs a local linear transform, learning selectively increases signal direction alignment (blue) while simultaneously decreasing noise direction alignment (orange). …"
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    (A) Network map of the top ten anti-AD core targets and the top 30 KEGG pathways. The color of the pathway nodes changed from pink to light pink as the DC value decreased. (B) 19 core pathways with DC values (ranked by DC>  average value of (4.933)). حسب Shakeel Ahmad Khan (13202394)

    منشور في 2025
    "…The color of the pathway nodes changed from pink to light pink as the DC value decreased. (B) 19 core pathways with DC values (ranked by DC>  average value of (4.933)).…"
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    Scheme of g-λ model with larger values λ. حسب Zhanfeng Fan (20390992)

    منشور في 2024
    "…And if the value of λ assumes larger values, the distortion in the shape of the transmitted wave is associated with the plastic deformation in the uncoupled rock mass. …"
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    Biases in larger populations. حسب Sander W. Keemink (21253563)

    منشور في 2025
    "…<p>(<b>A</b>) Maximum absolute bias vs the number of neurons in the population for the Bayesian decoder. …"
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    Table of values for <i>p.</i> حسب Long Di (9977453)

    منشور في 2025
    "…Furthermore, a probabilistic obstacle motion prediction framework is established through motion pattern analysis to actively optimize the robot’s motion strategy and reduce tracking errors. Simulation-based experimental results demonstrate that, under complex obstacle motion scenarios, the proposed method achieves a 55.8% reduction in trajectory tracking error compared with recently proposed improved APF methods and a 41.5% decrease relative to Dynamic Movement Primitives (DMP) baselines. …"
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