Search alternatives:
increase decrease » increased release (Expand Search), increased crash (Expand Search)
we decrease » _ decrease (Expand Search), nn decrease (Expand Search), mean decrease (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
increase decrease » increased release (Expand Search), increased crash (Expand Search)
we decrease » _ decrease (Expand Search), nn decrease (Expand Search), mean decrease (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
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5041
Major hyperparameters of RF-MLPR.
Published 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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5042
Results of RF algorithm screening factors.
Published 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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5043
Schematic diagram of the basic principles of SVR.
Published 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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5044
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5045
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5046
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5047
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5048
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5049
Comparison results of error between indoor running path and theoretical path of the robot dog.
Published 2025Subjects: -
5050
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5051
Comparison of position trajectories and truth values of different algorithms.
Published 2025Subjects: -
5052
Comparison of position trajectories and truth values of different algorithms.
Published 2025Subjects: -
5053
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5054
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5055
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5056
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5057
Positioning error results of different algorithms in the urban nav dataset.
Published 2025Subjects: -
5058
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5059
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5060
Comparison of positioning results between different algorithms in two scenarios.
Published 2025Subjects: