يعرض 1 - 20 نتائج من 5,000 نتيجة بحث عن '(( significantly ((less decrease) OR (greater decrease)) ) OR ( significant processes decrease ))', وقت الاستعلام: 0.50s تنقيح النتائج
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    Shot peening process parameters. حسب Huashen Guan (20454677)

    منشور في 2024
    الموضوعات:
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    Specimen packaging process. حسب Zhezhe Zhang (19704587)

    منشور في 2024
    "…Under the same <i>JRC</i>, σ<sub><i>i</i></sub> increases with the increase of τ<sub>1</sub>, and Δσ<sub>n</sub> decreases with the increasing τ<sub>1</sub>. Under the same <i>JRC</i> and σ<sub><i>i</i></sub>, τ<sub><i>i</i></sub> is significantly smaller under the UNLCSL path than the CNL path. …"
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    Preparation process of concrete joint specimens. حسب Zhezhe Zhang (19704587)

    منشور في 2024
    "…Under the same <i>JRC</i>, σ<sub><i>i</i></sub> increases with the increase of τ<sub>1</sub>, and Δσ<sub>n</sub> decreases with the increasing τ<sub>1</sub>. Under the same <i>JRC</i> and σ<sub><i>i</i></sub>, τ<sub><i>i</i></sub> is significantly smaller under the UNLCSL path than the CNL path. …"
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    Flame binarization image processing flow. حسب Lei Bai (631944)

    منشور في 2025
    الموضوعات:
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    Summary map of all contacts with statistically significant SVM classifications. حسب Alexander P. Rockhill (6053618)

    منشور في 2024
    "…Yellow reflects high classification accuracy, while dark blue represents less robust classification accuracy. Time-frequency points with no significant classification value are white.…"
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    Pseudo code for coupling model execution process. حسب Jintao Li (448681)

    منشور في 2024
    "…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R<sup>2</sup> value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …"
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