بدائل البحث:
significantly predicted » significantly reduced (توسيع البحث), significantly reduce (توسيع البحث), significant predictor (توسيع البحث)
predicted processing » predicted proteins (توسيع البحث), product processing (توسيع البحث), predicted pressure (توسيع البحث)
increase decrease » increased release (توسيع البحث)
significantly predicted » significantly reduced (توسيع البحث), significantly reduce (توسيع البحث), significant predictor (توسيع البحث)
predicted processing » predicted proteins (توسيع البحث), product processing (توسيع البحث), predicted pressure (توسيع البحث)
increase decrease » increased release (توسيع البحث)
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Predictors of coronary hyperemic DPV decrease after percutaneous coronary intervention.
منشور في 2024الموضوعات: -
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Data from: Colony losses of stingless bees increase in agricultural areas, but decrease in forested areas
منشور في 2025"…We found that colony losses during the rainy season decreased with higher abundance of forested areas and increased with higher abundance of agricultural area around meliponaries. …"
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Elman and SGWO-Elman optimization process.
منشور في 2023"…The results show: (1) the global convergence probability of SGWO was 1, and its process was a finite homogeneous Markov chain with an absorption state; (2) SGWO not only has better optimization performance when solving complex functions of different dimensions, but also when applied to Elman for parameter optimization, SGWO can significantly optimize the network structure and SGWO-Elman has accurate prediction performance.…"
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Pseudo code for coupling model execution process.
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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