بدائل البحث:
significantly longer » significantly lower (توسيع البحث), significantly larger (توسيع البحث), significantly higher (توسيع البحث)
significantly teer » significantly better (توسيع البحث), significantly weaker (توسيع البحث), significantly lower (توسيع البحث)
longer decrease » larger decrease (توسيع البحث), linear decrease (توسيع البحث), largest decrease (توسيع البحث)
teer decrease » mean decrease (توسيع البحث), greater decrease (توسيع البحث)
significantly longer » significantly lower (توسيع البحث), significantly larger (توسيع البحث), significantly higher (توسيع البحث)
significantly teer » significantly better (توسيع البحث), significantly weaker (توسيع البحث), significantly lower (توسيع البحث)
longer decrease » larger decrease (توسيع البحث), linear decrease (توسيع البحث), largest decrease (توسيع البحث)
teer decrease » mean decrease (توسيع البحث), greater decrease (توسيع البحث)
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201
Sample of study stimuli by content condition.
منشور في 2024"…</p><p>Results</p><p>The CI campaign had significantly higher perceived cultural relevance (M = 4.61) than the general audience (M = 3.64) or control (M = 3.66; p’s<0.05) campaigns. …"
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202
Major hyperparameters of RF-SVR.
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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203
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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204
Major hyperparameters of RF-MLPR.
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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205
Results of RF algorithm screening factors.
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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206
Schematic diagram of the basic principles of SVR.
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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207
Raw data_clean.
منشور في 2025"…Conversely, being overweight or obese is associated with lower CRF, which can lead to decreased daily energy expenditure and reduced physical activity. …"
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208
Experimental design.
منشور في 2025"…Conversely, being overweight or obese is associated with lower CRF, which can lead to decreased daily energy expenditure and reduced physical activity. …"
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209
Characterization of the participants.
منشور في 2025"…Conversely, being overweight or obese is associated with lower CRF, which can lead to decreased daily energy expenditure and reduced physical activity. …"
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210
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211
Experimental procedures.
منشور في 2025"…For ipsilateral erector spinae (ES) to rectus abdominis (RA) ratio, significant time effect (p = 0.022), between-group differences (p = 0.031), and real-time reduction during forward walking in left swing phase, and significant between-group differences (p = 0.024), time-and-group interaction effect (p = 0.009), and real-time increase during backward walking in right swing phase were noted. …"
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212
Experimental procedures.
منشور في 2025"…For ipsilateral erector spinae (ES) to rectus abdominis (RA) ratio, significant time effect (p = 0.022), between-group differences (p = 0.031), and real-time reduction during forward walking in left swing phase, and significant between-group differences (p = 0.024), time-and-group interaction effect (p = 0.009), and real-time increase during backward walking in right swing phase were noted. …"
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213
Supplementary file of datasets.
منشور في 2025"…For ipsilateral erector spinae (ES) to rectus abdominis (RA) ratio, significant time effect (p = 0.022), between-group differences (p = 0.031), and real-time reduction during forward walking in left swing phase, and significant between-group differences (p = 0.024), time-and-group interaction effect (p = 0.009), and real-time increase during backward walking in right swing phase were noted. …"
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214
Cox risk curve.
منشور في 2025"…Under different weather conditions, compared to sunny days, parking duration is longer during moderate rain, with the probability of vehicles departing decreased by 8.6%, whereas during heavy rain, parking duration is shorter, with the probability of vehicles departing increased by 3%. …"
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215
Weather factor dummy variable.
منشور في 2025"…Under different weather conditions, compared to sunny days, parking duration is longer during moderate rain, with the probability of vehicles departing decreased by 8.6%, whereas during heavy rain, parking duration is shorter, with the probability of vehicles departing increased by 3%. …"
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216
Day factor dummy variable.
منشور في 2025"…Under different weather conditions, compared to sunny days, parking duration is longer during moderate rain, with the probability of vehicles departing decreased by 8.6%, whereas during heavy rain, parking duration is shorter, with the probability of vehicles departing increased by 3%. …"
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217
Desensitized original data.
منشور في 2025"…Under different weather conditions, compared to sunny days, parking duration is longer during moderate rain, with the probability of vehicles departing decreased by 8.6%, whereas during heavy rain, parking duration is shorter, with the probability of vehicles departing increased by 3%. …"
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218
Cox survival function curve.
منشور في 2025"…Under different weather conditions, compared to sunny days, parking duration is longer during moderate rain, with the probability of vehicles departing decreased by 8.6%, whereas during heavy rain, parking duration is shorter, with the probability of vehicles departing increased by 3%. …"
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219
Data sample example.
منشور في 2025"…Under different weather conditions, compared to sunny days, parking duration is longer during moderate rain, with the probability of vehicles departing decreased by 8.6%, whereas during heavy rain, parking duration is shorter, with the probability of vehicles departing increased by 3%. …"
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220
The PL estimation result.
منشور في 2025"…Under different weather conditions, compared to sunny days, parking duration is longer during moderate rain, with the probability of vehicles departing decreased by 8.6%, whereas during heavy rain, parking duration is shorter, with the probability of vehicles departing increased by 3%. …"